Jobs

DeepX is looking for an experienced Data Engineer to drive our data integration initiatives. In this role, you will connect, transform, and prepare complex datasets to support centralized reporting and actionable business insights. Leveraging modern cloud-based technologies, data orchestration frameworks, and API integrations, you will play a pivotal role in ensuring our data infrastructure meets the evolving needs of our organization.

Key Responsibilities

• Architect, build, and maintain scalable and reliable ETL/ELT pipelines to integrate data from diverse international sources.
• Engineer data transformations that convert raw, complex data into clean, analysis-ready formats suitable for downstream analytics.
• Leverage the Google Cloud Platform (GCP) suite to build and manage scalable data storage and processing solutions, ensuring optimal security, reliability, and performance.
• Orchestrate complex data workflows using Apache Airflow, developing and maintaining robust DAGs for scheduling and monitoring.
• Troubleshoot and resolve issues within data pipelines and optimize workflow scheduling to guarantee timely data availability.
• Independently integrate with third-party services by interpreting API documentation, managing authentication, and developing custom data extraction solutions.
• Master Google Analytics 4's BigQuery export, structuring raw event data by flattening nested fields (e.g., event_params, user_properties) into query-optimized tables.
• Partner with our Business Intelligence teams to align data models and pipelines, seamlessly feeding into visualization tools like Looker Studio, DOMO, and Looker.
• Provide dedicated data support for dashboards, analytical projects, and ad-hoc reporting.
• Integrate and manage modern data connector tools, such as Stitch Data, and stay current with emerging technologies to enhance our data capabilities.
• Collaborate effectively with data analysts, data scientists, and other cross-functional teams to translate business needs into technical specifications.
• Curate and maintain comprehensive documentation for all data workflows, architectural designs, and transformation logic.
• Implement rigorous data validation, monitoring, and testing strategies to ensure data integrity and continuously improve pipeline performance and cost-efficiency.

Qualifications

• A minimum of 3 years of professional experience in a data engineering role, preferably with exposure to international datasets.
• Deep, hands-on experience with the Google Cloud Platform (GCP) ecosystem.
• Demonstrable expertise in orchestrating data pipelines with Apache Airflow, including DAG development and maintenance.
• Solid background in building production-grade ETL/ELT pipelines and utilizing connector tools like Stitch Data.
• Proven ability to work with APIs, from reading documentation to implementing data extraction logic.
• Experience handling Google Analytics 4 BigQuery exports, specifically with flattening nested data structures.
• Proficiency in SQL and at least one programming language (e.g., Python, Java, or Scala) for data manipulation and automation.
• Familiarity with BI platforms (Looker Studio, DOMO, Looker) and supporting BI team requirements.
• Proficiency with version control systems, particularly Git.
• Strong problem-solving skills with the ability to translate business requirements into technical solutions and optimize complex data processes.
• Excellent communication and collaboration skills, with the ability to work effectively in an international team environment.
• A proactive and detail-oriented mindset with a commitment to data quality and performance.
• English proficiency: Upper-Intermediate or higher.

About DeepX

DeepX is an R&D intensive and innovation-driven consortium that provides Artificial Intelligence-powered Computer Vision solutions for businesses. To find out more about us, please visit: https://deepxhub.com/

We’re building a large-scale data analytics ecosystem powered by Microsoft Azure and Power BI. Our team integrates, transforms, and visualizes data from multiple sources to support critical business decisions. Data quality is one of our top priorities, and we’re seeking an engineer who can help us enhance the reliability, transparency, and manageability of our data landscape. 

Your responsibilities: 

• Develop and maintain data quality monitoring frameworks within the Azure ecosystem (Data Factory, Data Lake, Databricks). 
• Design and implement data quality checks, including validation, profiling, cleansing, and standardization. 
• Detect data anomalies and design alerting systems (rules, thresholds, automation). 
• Collaborate with Data Engineers, Analysts, and Business stakeholders to define data quality criteria and expectations. 
• Ensure high data accuracy and integrity for Power BI reports and dashboards. 
• Document data validation processes and recommend improvements to data sources. 

Requirements: 

• 3+ years of experience in a Data Quality, Data Engineering, or BI Engineering role. 
• Hands-on experience with Microsoft Azure services (Data Factory, SQL Database, Data Lake). 
• Advanced SQL skills (complex queries, optimization, data validation). 
• Familiarity with Power BI or similar BI tools. 
• Understanding of DWH principles and ETL/ELT pipelines. 
• Experience with data quality frameworks and metrics (completeness, consistency, timeliness). 
• Knowledge of Data Governance, Master Data Management, and Data Lineage concepts. 

Would be a plus: 

• Experience with Databricks or Apache Spark. 
• DAX and Power Query (M) knowledge. 
• Familiarity with DataOps or DevOps principles in a data environment. 
• Experience in creating automated data quality dashboards in Power BI. 

Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps, FinOps, and GenAI support that drives real results.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for a Senior Data Engineer to play a key role in building our Data & Analytics practice and delivering modern data solutions on AWS for our clients. In this role, you'll be a customer-facing, hands-on technical engineer who designs and implements end-to-end data pipelines and analytics platforms using AWS services like AWS Glue, Amazon OpenSearch Service, Amazon Redshift, and Amazon QuickSight. From migrating legacy ETL workflows to AWS Glue to building scalable data lakes for AI/ML training, you'll ensure our customers can unlock the full value of their data. You’ll work closely with client stakeholders (from startup founders and CTOs to data engineers) to create secure, cost-efficient architectures that drive real business impact.

📍 Work location - remote from Ukraine

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• Design, develop, and deploy AWS-based data and analytics solutions to meet customer requirements. Ensure architectures are highly available, scalable, and cost-efficient.
• Develop dashboards and analytics reports using Amazon QuickSight or equivalent BI tools.
• Migrate and modernize existing data workflows to AWS. Re-architect legacy ETL pipelines to AWS Glue and move on-premises data systems to Amazon OpenSearch/Redshift for improved scalability and insights.
• Build and manage multi-modal data lakes and data warehouses for analytics and AI. Integrate structured and unstructured data on AWS (e.g. S3, Redshift) to enable advanced analytics and generative AI model training using tools like SageMaker.
• Implement infrastructure automation and CI/CD for data projects. Use Infrastructure as Code (Terraform) and DevOps best practices to provision AWS resources and continuously integrate/deploy data pipeline code.
• Lead customer workshops and proof-of-concepts (POCs) to demonstrate proposed solutions. Run technical sessions (architecture whiteboards, Well-Architected reviews) to validate designs and accelerate customer adoption.
• Collaborate with engineering teams (Data Scientist, DevOps and MLOps teams) and stakeholders to deliver projects successfully. Ensure solutions follow AWS best practices and security guidelines, and guide client teams in implementing according to the plan.

• Stay up-to-date on emerging data technologies and mentor team members. Continuously learn new AWS services (e.g. AWS Bedrock, Lake Formation) and industry trends, and share knowledge to improve our delivery as we grow the Data & Analytics practice.

   

Requirements

• 5+ years of experience in data engineering, data analytics, or a related field, including 3+ years of hands-on AWS experience (designing, building, and maintaining data solutions on AWS).
• Production experience with AWS cloud and data services, including building solutions at scale with tools like AWS Glue, Amazon Redshift, Amazon S3, Amazon Kinesis, Amazon OpenSearch Service, etc.
• Skilled in AWS analytics and dashboards tools – hands-on expertise with services such as Amazon QuickSight or other BI tools (Tableau, Power BI) and Amazon Athena.
• Experience with ETL pipelines – ability to build ETL/ELT workflows (using AWS Glue, Spark, Python, SQL).
•  Experience with data warehousing and data lakes - ability to design and optimize data lakes (on S3), Amazon Redshift for data warehousing, and Amazon OpenSearch for log/search analytics.
• Proficiency in programming (Python/PySpark) and SQL skills for data processing and analysis.
• Understanding of cloud security and data governance best practices (encryption, IAM, data privacy).
• Excellent communication skills with an ability to explain complex data concepts in clear terms. Comfortable working directly with clients and guiding technical discussions.
• Proven ability to lead end-to-end technical engagements and work effectively in fast-paced, Agile environments.
• AWS certification – AWS certifications, especially in Data Analytics or Machine Learning are a plus.

• DevOps/MLOps knowledge – experience with Infrastructure as Code (Terraform), CI/CD pipelines, containerization, and AWS AI/ML services (SageMaker, Bedrock) is a plus.

   

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes
• Soft skills training

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognising the value you bring to our team.

Biosphere Corporation is one of the largest producers and distributors of household, hygiene, and professional products in Eastern Europe and Central Asia (TM Freken BOK, Smile, Selpak, Vortex, Novita, PRO service, and many others). We are inviting an IT Infrastructure Administrator to join our team.

Key responsibilities:

• Administration of Active Directory
• Managing group policies
• Managing services via PowerShell
• Administration of VMWare platform
• Administration of Azure Active Directory
• Administration of Exchange 2016/2019 mail servers
• Administration of Exchange Online
• Administration of VMWare Horizon View

Required professional knowledge and skills:

• Experience in writing automation scripts (PowerShell, Python, etc.)
• Skills in working with Azure Active Directory (user and group creation, report generation, configuring synchronization between on-premise and cloud AD)
• Skills in Exchange PowerShell (mailbox creation, search and removal of emails based on criteria, DAG creation and management)
• Experience with Veeam Backup & Replication, VMWare vSphere (vCenter, DRS, vMotion, HA), VMWare Horizon View
• Windows Server 2019/2025 (installation, configuration, and adaptation)
• Diagnostics and troubleshooting
• Working with anti-spam systems
• Managing mail transport systems (exim) and monitoring systems (Zabbix)

We offer:

• Interesting projects and tasks
• Competitive salary (discussed during the interview)
• Convenient work schedule: Mon–Fri, 9:00–18:00; partial remote work possible
• Official employment, paid vacation, and sick leave
• Probation period — 2 months
• Professional growth and training (internal training, reimbursement for external training programs)
• Discounts on Biosphere Corporation products
• Financial assistance (in cases of childbirth, medical treatment, force majeure, or circumstances caused by wartime events, etc.)

Office address: Dnipro, Zaporizke Highway 37 (Right Bank, Topol-1 district).

Learn more about Biosphere Corporation, our strategy, mission, and values at:
http://biosphere-corp.com/
https://www.facebook.com/biosphere.corporation/

Join our team of professionals!

By submitting your CV for this vacancy, you consent to the use of your personal data in accordance with the current legislation of Ukraine.
If your application is successful, we will contact you within 1–2 business days.

Who we are?
We are building a next-generation AI-native sales automation platform for B2B teams. Our goal is to change the very paradigm of how people interact with business applications.

Manual data entry becomes a thing of the past as the platform proactively connects to your communication and information channels. It seamlessly captures, structures, and transforms data into real-time, actionable awareness.

You no longer work for the tool. The tool works for you, anticipating your needs, surfacing the right context at the right moment, and guiding your next steps with intelligence and precision.

Our vision is to give teams an always-on AI-driven partner that lets them focus entirely on creating value and closing deals.
 

Philosophy

We value open-mindedness, rapid delivery and impact. You’re not just coding features-you shape architecture, UX, and product direction. Autonomy, accountability, and a startup builder’s mindset are essential.
 

Requirements

• Strong backend: Python, FastAPI, Webhooks, Docker, Kubernetes, Git, CI/CD.
• Hands-on with OpenAI-family LLMs, LangChain/LangGraph/LangSmith, prompt engineering, agentic RAG, vector stores (Azure AI Search, Pinecone, Neo4j, hFAISS).
• SQL, Pandas, Graph DBs (Neo4j), NetworkX, advanced ETL/data cleaning, Kafka/Azure EventHub.
• Proven experience building and operating retrieval-augmented generation (RAG) pipelines.
• Familiarity with graph algorithms (community detection, similarity, centrality).
• Good English (documentation, API, teamwork).
   

Nice to Have

• Generative UI (React).
• Multi-agent LLM frameworks.
• Big Data pipelines in cloud (Azure preferred).
• Production-grade ML, NLP engineering, graph ML.
   

Responsibilities

• Design, deploy, and maintain GenAI/RAG pipelines for the product
• Integrate LLM/agentic assistants into user business flows.
• Source, ingest, cleanse, and enrich external data streams.
• Build vector search, embedding stores, and manage knowledge graphs.
• Explore and implement new ML/GenAI frameworks.
• Mentor developers and encourage team knowledge-sharing.
   

What else is important:

• Startup drive, proactivity, independence.
• Willingness to relocate/freedom to travel in Europe; full time.
• Eagerness to integrate latest AI frameworks into real-world production.
   

Our Team

Agile, tight-knit product group (5–6 experts) with deep experience in SaaS, AI, graph data, and cloud delivery. We move fast, give each member autonomy, and engineer for impact- not just features.
 

Who takes a final decision:

The team makes the decision based on a technical interview.
 

Our benefits

• Startup culture: minimal bureaucracy, maximum flexibility
• Remote-first: work from anywhere
• Unlimited vacation — we value results, not hours spent
• Opportunity to grow together with an AI-first product company
• Direct impact on a breakthrough AI-native product
   

Recruitment process

1. HR interview (VP Team) — Technical prescreen (Q&A)
2. Technical interview with CTO/Data Officer (real-life case)
3. Offer

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:
Our client is an IT company that develops technological solutions and products to help companies reach their full potential and meet the needs of their users. The team comprises over 600 specialists in IT and Digital, with solid expertise in various technology stacks necessary for creating complex solutions.

About the role:
We are looking for a Data Engineer (NLP-Focused) to build and optimize the data pipelines that fuel the Ukrainian LLM and NLP initiatives. In this role, you will design robust ETL/ELT processes to collect, process, and manage large-scale text and metadata, enabling the Data Scientists and ML Engineers to develop cutting-edge language models.

You will work at the intersection of data engineering and machine learning, ensuring that the datasets and infrastructure are reliable, scalable, and tailored to the needs of training and evaluating NLP models in a Ukrainian language context.

Requirements:
- Education & Experience: 3+ years of experience as a Data Engineer or in a similar role, building data-intensive pipelines or platforms. A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is preferred. Experience supporting machine learning or analytics teams with data pipelines is a strong advantage.
- NLP Domain Experience: Prior experience handling linguistic data or supporting NLP projects (e.g., text normalization, handling different encodings, tokenization strategies). Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given the project’s focus.
Understanding of FineWeb2 or a similar processing pipeline approach.
- Data Pipeline Expertise: Hands-on experience designing ETL/ELT processes, including extracting data from various sources, using transformation tools, and loading into storage systems. Proficiency with orchestration frameworks like Apache Airflow for scheduling workflows. Familiarity with building pipelines for unstructured data (text, logs) as well as structured data.
- Programming & Scripting: Strong programming skills in Python for data manipulation and pipeline development. Experience with NLP packages (spaCy, NLTK, langdetect, fasttext, etc.). Experience with SQL for querying and transforming data in relational databases. Knowledge of Bash or other scripting for automation tasks. Writing clean, maintainable code and using version control (Git) for collaborative development.
- Databases & Storage: Experience working with relational databases (e.g., PostgreSQL, MySQL), including schema design and query optimization. Familiarity with NoSQL or document stores (e.g., MongoDB) and big data technologies (HDFS, Hive, Spark) for large-scale data is a plus. Understanding of or experience with vector databases (e.g., Pinecone, FAISS) is beneficial, as the NLP applications may require embedding storage and fast similarity search.
- Cloud Infrastructure: Practical experience with cloud platforms (AWS, GCP, or Azure) for data storage and processing. Ability to set up services such as S3/Cloud Storage, data warehouses (e.g., BigQuery, Redshift), and use cloud-based ETL tools or serverless functions. Understanding of infrastructure-as-code (Terraform, CloudFormation) to manage resources is a plus.
- Data Quality & Monitoring: Knowledge of data quality assurance practices. Experience implementing monitoring for data pipelines (logs, alerts) and using CI/CD tools to automate pipeline deployment and testing. An analytical mindset to troubleshoot data discrepancies and optimize performance bottlenecks.
- Collaboration & Domain Knowledge: Ability to work closely with data scientists and understand the requirements of machine learning projects. Basic understanding of NLP concepts and the data needs for training language models, so you can anticipate and accommodate the specific forms of text data and preprocessing they require. Good communication skills to document data workflows and to coordinate with team members across different functions.

Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines for gathering, transforming, and storing large volumes of text data and related information.
- Ensure pipelines are efficient and can handle data from diverse sources (e.g., web crawls, public datasets, internal databases) while maintaining data integrity.
- Implement web scraping and data collection services to automate the ingestion of text and linguistic data from the web and other external sources. This includes writing crawlers or using APIs to continuously collect data relevant to the language modeling efforts.
- Implementation of NLP/LLM-specific data processing: cleaning and normalization of text, like filtering of toxic content, de-duplication, de-noising, detection, and deletion of personal data.
- Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
- Set up and manage cloud-based data infrastructure for the project. Configure and maintain data storage solutions (data lakes, warehouses) and processing frameworks (e.g., distributed compute on AWS/GCP/Azure) that can scale with growing data needs.
- Automate data processing workflows and ensure their scalability and reliability.
- Use workflow orchestration tools like Apache Airflow to schedule and monitor data pipelines, enabling continuous and repeatable model training and evaluation cycles.
- Maintain and optimize analytical databases and data access layers for both ad-hoc analysis and model training needs.
- Work with relational databases (e.g., PostgreSQL) and other storage systems to ensure fast query performance and well-structured data schemas.
- Collaborate with Data Scientists and NLP Engineers to build data features and datasets for machine learning models.
- Provide data subsets, aggregations, or preprocessing as needed for tasks such as language model training, embedding generation, and evaluation.
- Implement data quality checks, monitoring, and alerting. Develop scripts or use tools to validate data completeness and correctness (e.g., ensuring no critical data gaps or anomalies in the text corpora), and promptly address any pipeline failures or data issues. Implement data version control.
- Manage data security, access, and compliance.
- Control permissions to datasets and ensure adherence to data privacy policies and security standards, especially when dealing with user data or proprietary text sources.

The company offers:
- Competitive salary.
- Equity options in a fast-growing AI company.
- Remote-friendly work culture.
- Opportunity to shape a product at the intersection of AI and human productivity.
- Work with a passionate, senior team building cutting-edge tech for real-world business use.

About us:
Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client:
Our client is an IT company that develops technological solutions and products to help companies reach their full potential and meet the needs of their users. The team comprises over 600 specialists in IT and Digital, with solid expertise in various technology stacks necessary for creating complex solutions.

About the role:
We are looking for a Data Engineer (NLP-Focused) to build and optimize the data pipelines that fuel the Ukrainian LLM and NLP initiatives. In this role, you will design robust ETL/ELT processes to collect, process, and manage large-scale text and metadata, enabling the Data Scientists and ML Engineers to develop cutting-edge language models.

You will work at the intersection of data engineering and machine learning, ensuring that the datasets and infrastructure are reliable, scalable, and tailored to the needs of training and evaluating NLP models in a Ukrainian language context.

Requirements:
- Education & Experience: 3+ years of experience as a Data Engineer or in a similar role, building data-intensive pipelines or platforms. A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is preferred. Experience supporting machine learning or analytics teams with data pipelines is a strong advantage.
- NLP Domain Experience: Prior experience handling linguistic data or supporting NLP projects (e.g., text normalization, handling different encodings, tokenization strategies). Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given the project’s focus.
Understanding of FineWeb2 or a similar processing pipeline approach.
- Data Pipeline Expertise: Hands-on experience designing ETL/ELT processes, including extracting data from various sources, using transformation tools, and loading into storage systems. Proficiency with orchestration frameworks like Apache Airflow for scheduling workflows. Familiarity with building pipelines for unstructured data (text, logs) as well as structured data.
- Programming & Scripting: Strong programming skills in Python for data manipulation and pipeline development. Experience with NLP packages (spaCy, NLTK, langdetect, fasttext, etc.). Experience with SQL for querying and transforming data in relational databases. Knowledge of Bash or other scripting for automation tasks. Writing clean, maintainable code and using version control (Git) for collaborative development.
- Databases & Storage: Experience working with relational databases (e.g., PostgreSQL, MySQL), including schema design and query optimization. Familiarity with NoSQL or document stores (e.g., MongoDB) and big data technologies (HDFS, Hive, Spark) for large-scale data is a plus. Understanding of or experience with vector databases (e.g., Pinecone, FAISS) is beneficial, as the NLP applications may require embedding storage and fast similarity search.
- Cloud Infrastructure: Practical experience with cloud platforms (AWS, GCP, or Azure) for data storage and processing. Ability to set up services such as S3/Cloud Storage, data warehouses (e.g., BigQuery, Redshift), and use cloud-based ETL tools or serverless functions. Understanding of infrastructure-as-code (Terraform, CloudFormation) to manage resources is a plus.
- Data Quality & Monitoring: Knowledge of data quality assurance practices. Experience implementing monitoring for data pipelines (logs, alerts) and using CI/CD tools to automate pipeline deployment and testing. An analytical mindset to troubleshoot data discrepancies and optimize performance bottlenecks.
- Collaboration & Domain Knowledge: Ability to work closely with data scientists and understand the requirements of machine learning projects. Basic understanding of NLP concepts and the data needs for training language models, so you can anticipate and accommodate the specific forms of text data and preprocessing they require. Good communication skills to document data workflows and to coordinate with team members across different functions.

Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines for gathering, transforming, and storing large volumes of text data and related information.
- Ensure pipelines are efficient and can handle data from diverse sources (e.g., web crawls, public datasets, internal databases) while maintaining data integrity.
- Implement web scraping and data collection services to automate the ingestion of text and linguistic data from the web and other external sources. This includes writing crawlers or using APIs to continuously collect data relevant to the language modeling efforts.
- Implementation of NLP/LLM-specific data processing: cleaning and normalization of text, like filtering of toxic content, de-duplication, de-noising, detection, and deletion of personal data.
- Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.
- Set up and manage cloud-based data infrastructure for the project. Configure and maintain data storage solutions (data lakes, warehouses) and processing frameworks (e.g., distributed compute on AWS/GCP/Azure) that can scale with growing data needs.
- Automate data processing workflows and ensure their scalability and reliability.
- Use workflow orchestration tools like Apache Airflow to schedule and monitor data pipelines, enabling continuous and repeatable model training and evaluation cycles.
- Maintain and optimize analytical databases and data access layers for both ad-hoc analysis and model training needs.
- Work with relational databases (e.g., PostgreSQL) and other storage systems to ensure fast query performance and well-structured data schemas.
- Collaborate with Data Scientists and NLP Engineers to build data features and datasets for machine learning models.
- Provide data subsets, aggregations, or preprocessing as needed for tasks such as language model training, embedding generation, and evaluation.
- Implement data quality checks, monitoring, and alerting. Develop scripts or use tools to validate data completeness and correctness (e.g., ensuring no critical data gaps or anomalies in the text corpora), and promptly address any pipeline failures or data issues. Implement data version control.
- Manage data security, access, and compliance.
- Control permissions to datasets and ensure adherence to data privacy policies and security standards, especially when dealing with user data or proprietary text sources.

The company offers:
- Competitive salary.
- Equity options in a fast-growing AI company.
- Remote-friendly work culture.
- Opportunity to shape a product at the intersection of AI and human productivity.
- Work with a passionate, senior team building cutting-edge tech for real-world business use.

We are currently seeking a Solution Architect who specializes in data-driven projects to become a part of our Data Practice team in Ukraine.

Responsibilities

• Architect data analytics solutions by leveraging the big data technology stack
• Develop and present detailed technical solution architecture documents
• Collaborate with business stakeholders to define solution requirements and explore case studies/scenarios for future solutions
• Perform solution architecture reviews/audits, compute and present ROI
• Manage the implementation of solutions from setting project requirements and objectives to the solution “go-live”
• Engage in the entire spectrum of pre-sale activities, including direct communication with customers, RFP processing, crafting implementation proposals, and solution architecture presentations to clients, as well as participation in technical discussions with client representatives
• Construct and adhere to a personal education plan in technology stack and solution architecture
• Develop a robust understanding of industry trends and best practices
• Participate in the acquisition of new clients to expand EPAM’s business in the big data sector

Requirements

• Minimum of 7 years' experience required
• Proficiency in hands-on roles as a Big Data Architect with a strong design/development background in Java, Scala, or Python
• Background in delivering data analytics projects and architecture guidelines
• Skills in big data solutions, both on-premises and on cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud
• Production project experience with at least one big data technology is essential
• Batch processing expertise: Hadoop, MapReduce/Spark/Hive
• Understanding of NoSQL databases: Cassandra, HBase, Accumulo, Kudu
• Familiarity with Agile development methodology, particularly Scrum
• Competency in client communication and pre-sales business-consulting to large enterprise environments
• Experience within a consulting firm and pre-sales backgrounds are highly desirable
• Upper-Intermediate level in English, both spoken and written (B2+)

We are Boosta — a holding IT company that creates, scales, and invests in digital businesses with global potential.
- Founded in 2014
- 600+ professionals
- Hundreds of thousands of users worldwide
Boosta’s portfolio includes a wide range of successful IT products, as well as projects focused on performance marketing.
Since 2022, the company’s ecosystem has included its own investment fund, Burner, which provides funding in the formats of Private Equity and Venture Builder.

We’re looking for a Data Engineer to join our team in the iGaming industry, where real-time insights, affiliate performance, and marketing analytics are at the center of decision-making. In this role, you’ll own and scale our data infrastructure, working across affiliate integrations, product analytics, and experimentation workflows. 
Your primary responsibilities will include building and maintaining data pipelines, implementing automated data validation, integrating external data sources via APIs, and creating dashboards to monitor data quality, consistency, and reliability. 
You’ll collaborate daily with the Affiliate Management team, Product Analysts, and Data Scientists to ensure the data powering our reports and models is clean, consistent, and reliable. 

Key Responsibilities 
● Design, develop, and maintain ETL/ELT pipelines to transform raw, multi-source data into clean, analytics-ready tables in Google BigQuery, using tools such as dbt for modular SQL transformations, testing, and documentation 
● Integrate and automate affiliate data workflows, replacing manual processes in collaboration with the related stakeholders 
● Proactively monitor and manage data pipelines using tools such as Airflow, with proper alerting and retry mechanisms in place 
● Emphasize data quality, consistency, and reliability by implementing robust validation checks 
● Build a Data Consistency Dashboard (in Looker Studio, Power BI, Tableau or Grafana) to track schema mismatches, partner anomalies, and source freshness, with built-in alerts and escalation logic 
● Ensure timely availability and freshness of all critical datasets, resolving latency and reliability issues quickly and sustainably 
● Control access to cloud resources, implement data governance policies, and ensure secure, structured access across internal teams 
● Monitor and optimize data infrastructure costs, particularly related to BigQuery usage, storage, and API-based ingestion 
● Document all pipelines, dataset structures, transformation logic, and data contracts clearly to support internal alignment and knowledge sharing 
● Build and maintain postback-based ingestion pipelines to support event-level tracking and attribution across the affiliate ecosystem 
● Collaborate closely with Data Scientists and Product Analysts to deliver high-quality, structured datasets for modeling, experimentation, and KPI reporting 

Skills & Experience 
● Strong proficiency in SQL and Python
● Experience with Google BigQuery and other GCP tools (e.g., Cloud Storage, Cloud Functions, Composer) 
● Proven ability to design, deploy, and scale ETL/ELT pipelines 
● Hands-on experience integrating and automating data from various platforms 
● Familiarity with postback tracking, attribution logic, and affiliate data reconciliation 
● Skilled in orchestration tools like Airflow or similar 
● Experience with visualization tools like Looker Studio, Power BI, Tableau, or Grafana for building dashboards for data quality monitoring and business needs 
● Experience with Git for version control and Docker 
● Exposure to iGaming data structures and KPIs is a strong advantage 
● Strong sense of data ownership, documentation, and operational excellence 
● Good communication skills with different stakeholders 
● Upper-intermediate English language proficiency 

HOW IT WORKS
Stage 1: CV and short questionary
Stage 2: pre-screen with a recruiter

Stage 3: test task
Stage 4: interview.

Stage 5: final intrview
Stage 6: reference check & offer!

WHAT WE OFFER

• 28 business days of paid off
• Flexible hours and the possibility to work remotely
• Medical insurance and mental health care
• Compensation for courses, trainings
• English classes and speaking clubs
• Internal library, educational events
• Outstanding corporate parties, teambuildings

Kyivstar.Tech team is looking for a new colleague for the role of ETL/RAID developer

What you will do

Development of functionality and ensuring the operation of processes:

• Creation of orders and aggregation processes using ETL/ WEDO RAID  
• Development of processes related to data processing, interaction with systems and support of existing processes 
• Testing processes and logic developed in streams
• Work on writing and correcting Batch file, Java-script, Python-script, work with API, CSV, TXT, XML, JSON

• Administration of test environments + provision of recommendations for process changes

   

Qualifications and experience needed

• At least 4 years of experience with SQL programming and development using ETL/ WEDO RAID tools

• Knowledge of Python, Java or similar programming languages ​​will be an advantage

   

What we offer

• Office or remote — it's up to you: you can work from anywhere, and we will arrange your workplace
• Remote onboarding
• Performance bonuses for everyone (annual or quarterly — depends on the role)
• We train employees: with the opportunity to learn through the company’s library, internal resources, and programs from partners
• Health and life insurance
• Wellbeing program and corporate psychologist
• Reimbursement of expenses for Kyivstar mobile communication

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We are seeking a dynamic Sales Executive to lead our sales efforts for GCP and GWS solutions across the EMEA and CEE regions. The ideal candidate will be a high-performing A-player with experience in SaaS sales, adept at navigating complex sales environments, and driven to exceed targets through strategic sales initiatives.

Requirements:

• Fluency in English and native Czech is essential;
• From 2 years of proven sales experience in SaaS/ IaaS fields, with a documented history of achieving and exceeding sales targets, particularly in enterprise sales;
• Sales experience on GCP and/or GWS specifically;
• Sales or technical certifications related to Cloud Solutions are advantageous;
• Experience in expanding new markets with outbound activities;
• Excellent communication, negotiation, and strategic planning abilities;
• Proficient in managing CRM systems and understanding their strategic importance in sales and customer relationship management.

Responsibilities:

• Develop and execute sales strategies for GCP and GWS solutions, targeting enterprise clients within the Cloud markets across EMEA and CEE;
• Identify and penetrate new enterprise market segments, leveraging GCP and GWS to improve client outcomes;
• Conduct high-level negotiations and presentations with major companies across Europe, focusing on the strategic benefits of adopting GCP and GWS solutions;
• Work closely with marketing and business development teams to align sales strategies with broader company goals;
• Continuously assess the competitive landscape and customer needs, adapting sales strategies to meet market demands and drive revenue growth.

Work conditions:

• Competitive Salary & Transparent Motivation: Receive a competitive base salary with commission on sales and performance-based bonuses, providing clear financial rewards for your success.
• Flexible Work Format: Work remotely with flexible hours, allowing you to balance your professional and personal life efficiently.
• Freedom to Innovate: Utilize multiple channels and approaches for sales, allowing you the freedom to find the best strategies for success.
• Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
• International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry. Expand your expertise by engaging with international markets across the EMEA and CEE regions.
• Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.
• When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
• Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes.

We are looking for a CloudOps Engineer to join our teams!
 

Requirements:

- 4+ years of experience with DevOps practices
- 3+ years of experience in public cloud platforms (AWS, GCP, GCore etc)
- Strong knowledge of Linux architecture and systems implementation
- Strong knowledge of IaC approach (Ansible, Terraform)
- Strong scripting skills in Bash, Python, or other automation languages
- Strong knowledge of Cloud based approach
- Knowledge of Kubernetes management
- Good understanding of networking concepts and protocols
- Experience in microservices architecture, distributed systems, and scaling production environments.
- Experience/awareness of automated DevOps activities, concepts, and toolsets.
- Experience with AWS Control Tower, Config, IAM and other technologies that enable high-level administration
- Experience building and maintaining CI/CD pipelines using tools like GitLab/GitHub CI
- Experience with AWS CloudWatch, GCP Cloud Monitoring, Prometheus, Grafana for monitoring and log aggregation
- Problem-solving and troubleshooting skills, ability to analyze complex systems and identify the causes of problems
- Preferable experience with GCP Cloud Resource management, IAM, Organization policies and other technologies that enable high-level administration

Will be plus:
- AWS Certified SysOps Administrator
- AWS Certified DevOps Engineer
- GCP Certified Cloud Engineer
- GCP Certified Cloud DevOps Engineer
- Similar Public Cloud certificates

Soft Skills:
- Team player
- Critical Thinking
- Good communicator
- Open to challenges and new opportunities
- Thirst for knowledge
- Time Management

Responsibilities:
- Support and evolution of the current public cloud infrastructure
- Automating repetitive tasks and processes in public cloud infrastructure
- Automation and improvement of current processes related to the administration and support of public clouds
- Implementation of new providers of public cloud services
- Collaborate with cross-functional teams to define cloud strategies, governance, and best practices.
- Conduct architectural assessments and provide recommendations for optimizing existing public cloud environments

Our benefits to you:
☘️An exciting and challenging job in a fast-growing holding, the opportunity to be part of a multicultural team of top professionals in Development, Architecture, Management, Operations, Marketing, Legal, Finance and more
🤝🏻Great working atmosphere with passionate experts and leaders, sharing a friendly culture and a success-driven mindset is guaranteed
🧑🏻‍💻Modern corporate equipment based on macOS or Windows and additional equipment are provided
🏖Paid vacations, sick leave, personal events days, days off
💵Referral program — enjoy cooperation with your colleagues and get the bonus
📚Educational programs: regular internal training sessions, compensation for external education, attendance of specialized global conferences
🎯Rewards program for mentoring and coaching colleagues
🗣Free internal English courses
✈️In-house Travel Service 
🦄Multiple internal activities: online platform for employees with quests, gamification, presents and news, PIN-UP clubs for movie / book / pets lovers and more
🎳Other benefits could be added based on your location

Our client is at the forefront of innovation in the gaming industry, leveraging data and AI to enhance player experiences and drive community engagement. We are seeking a passionate data engineer to join our dynamic team, dedicated to transforming data into actionable insights and enabling advanced AI applications.

As a Data Engineer, you will play an important role in designing, building, and optimizing data pipelines and architectures for AI and machine learning initiatives. You will work closely with AI/ML engineers and software developers on various tasks to effectively collect, store, and process data from multiple sources, including social media and in-game interactions.

Key Responsibilities

Data Infrastructure & Warehousing:

• Design and implement data pipelines using AWS Redshift, S3, and related AWS services
• Build ETL/ELT processes to ingest data from game servers, blockchain networks, and third-party APIs
• Optimize Redshift performance through query optimization, table design, and distribution strategies
• Implement data modeling best practices for dimensional and fact table structures
• Web3 & Blockchain Integration:
• Extract and process on-chain data from various blockchain networks (Ethereum, Polygon, BSC, etc.)
• Integrate NFT marketplace data, token transactions, and smart contract events
• Build real-time streaming pipelines for blockchain data using AWS Kinesis or similar services
• Ensure data accuracy and consistency across centralized game databases and decentralized blockchain data

Game Analytics & Metrics:

• Develop data models for player behavior, retention, monetization, and engagement metrics
• Create datasets supporting player lifecycle analysis, cohort studies, and revenue attribution
• Build data marts for game economy analytics, including token economics and NFT trading patterns
• Support A/B testing infrastructure and statistical analysis requirements
• Data Quality & Governance:
• Implement data validation, monitoring, and alerting systems
• Establish data lineage tracking and documentation standards
• Ensure compliance with data privacy regulations and Web3 security best practices
• Collaborate with data analysts and scientists to understand requirements and optimize data delivery
  
   

Required Qualifications

Technical Skills:

• 3-5 years of experience in data engineering or a related field
• Strong proficiency with AWS Redshift, including query optimization and performance tuning
• Experience with AWS ecosystem (S3, Lambda, Glue, Kinesis, CloudFormation/CDK)
• Proficiency in SQL and at least one programming language (Python, Scala, or Java)
• Experience with ETL tools and frameworks (Apache Airflow, dbt, AWS Glue)
• Understanding of data warehousing concepts and dimensional modeling

Additional Requirements:

• Experience with version control systems (Git) and CI/CD practices
• Strong problem-solving skills and attention to detail
• Excellent communication skills and ability to work in cross-functional teams
• Bachelor's degree in Computer Science, Data Engineering, or related field

Preferred Qualifications

• Experience with other cloud platforms (GCP BigQuery, Azure Synapse)
• Knowledge of machine learning pipelines and MLOps practices
• Familiarity with container technologies (Docker, Kubernetes)
• Experience with NoSQL databases (DynamoDB, MongoDB)
• Previous experience in the gaming industry or Web3/crypto projects
• Certifications in AWS or other relevant technologies

Nice to Have

Web3 & Gaming Knowledge:

• Basic understanding of blockchain technology, smart contracts, and DeFi protocols
• Familiarity with Web3 data sources (The Graph, Moralis, Alchemy APIs)
• Experience with gaming analytics metrics and player behavior analysis
• Knowledge of real-time data processing and streaming architectures

🎁 We offer:

• Medical Insurance in Ukraine and Multisport program in Poland;
• Flexible working hours;
• Offices in Ukraine;
• All official holidays;
• Paid vacation and sick leaves;
• Tax & accounting services for Ukrainian contractors;
• The company is ready to provide all the necessary equipment;
• English classes up to three times a week;
• Mentoring and Educational Programs;
• Regular Activities on a Corporate level (Incredible parties, Team Buildings, Sports Events, Table Games, Tech Events);
• Advanced Bonus System.

N-iX is looking for a Middle/Senior Data Engineer who would be involved in designing, implementing, and managing the new Data Lakehouse for our customer in the e-commerce domain. The ideal candidate has worked with data-related services in AWS, Snowflake, and experience in modern data approaches.   

Our Client is a global full-service e-commerce and subscription billing platform on a mission to simplify software sales everywhere. For nearly two decades, we’ve helped SaaS, digital goods, and subscription-based businesses grow by managing payments, global tax compliance, fraud prevention, and recurring revenue at scale. Our flexible, cloud-based platform, combined with consultative services, helps clients accelerate growth, reach new markets, and build long-term customer relationships.

Data is at the heart of everything we do — powering insights, driving innovation, and shaping business decisions. We are building a next-generation data platform, and we’re looking for a Senior Data Engineer to help us make it happen.

As a Data Engineer, you will play a key role in designing and building our new Data Lakehouse on AWS, enabling scalable, reliable, and high-quality data solutions. You will work closely with senior engineers, data architects, and product managers to create robust data pipelines, develop data products, and optimize storage solutions that support business-critical analytics and decision-making.

Responsibilities:

• Build and operate a modern Data Lakehouse on AWS (S3 + Iceberg) supporting ingestion, storage, transformation, and serving layers.
• Design and optimize ETL pipelines using PySpark, Airflow (MWAA), and Snowflake for scalability and cost efficiency.
• Automate workflows with Python scripts, integration validation, and monitoring across sources and layers.
• Implement and enforce data quality controls (Glue Data Quality, Great Expectations) and contribute to governance best practices.
• Collaborate with cross-functional teams (Data and Software Architects, Engineering Managers, Product Owners, and Data/Power BI Engineers) to refine data requirements and deliver trusted and actionable insights.
• Support CI/CD practices via GitLab, ensuring version-controlled, testable, and auditable data processes.
• Document data flows and business logic to maintain transparency, lineage, and knowledge transfer across teams.
• Continuously improve operational efficiency by troubleshooting issues, monitoring performance, and suggesting technical enhancements.
  
   

Requirements:

• 3+ years of hands-on experience in Data Engineering, preferably in lakehouse or hybrid architectures.
• Proficiency in PySpark for large-scale transformations across layered datasets.
• Experience with Airflow (MWAA) for orchestrating end-to-end pipelines, dependencies, and SLA-driven workloads.
• Knowledge of AWS services used in modern data platforms: S3 + Iceberg, Glue (Catalog + Data Quality), Athena, EMR.
• Experience in Snowflake for analytics serving and cross-platform ingestion.
• Proficiency in Python for automation, validation, and auxiliary data workflows.
• Understanding of data modeling principles and harmonization principles, including SCD handling and cross-source entity resolution.
• Familiarity with CI/CD pipelines in Git/GitLab, ensuring tested, version-controlled, and production-ready deployments.
• Experience working with BI ecosystems (e.g., Power BI, dbt-like transformations, semantic layers).
• Upper-Intermediate English or higher, with the ability to document and explain complex concepts.
  
   

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Description

You will be joining GlobalLogic’s Media and Entertainment (M&E) practice, a specialized team within a leading digital engineering company. Our practice is at the forefront of the media industry’s technological evolution, partnering with the world’s largest broadcasters, content creators, and distributors. We have a proven track record of engineering complex solutions, including cloud-based OTT platforms (like VOS360), Media/Production Asset Management (MAM/PAM) systems, software-defined broadcast infrastructure, and innovative contribution/distribution workflows.

This engagement is for a landmark cloud transformation project for a major client in the media sector. The objective is to architect the strategic migration of a large-scale linear broadcasting platform from its current foundation on AWS to Oracle Cloud Infrastructure (OCI). You will be a key advisor on a project aimed at modernizing critical broadcast operations, enhancing efficiency, and building a future-proof cloud architecture.

Requirements

We are seeking a seasoned cloud professional with a deep understanding of both cloud infrastructure and the unique demands of the media industry.

• Expert-Level OCI Experience: Proven hands-on experience designing, building, and managing complex enterprise workloads on Oracle Cloud Infrastructure (OCI).
• Cloud Migration Expertise: Demonstrable experience architecting and leading at least one significant cloud-to-cloud migration project, preferably from AWS to OCI.
• Strong Architectural Acumen: Deep understanding of cloud architecture principles across compute, storage, networking, security, and identity/access management.
• Client-Facing & Consulting Skills: Exceptional communication and presentation skills, with the ability to act as a credible and trusted advisor to senior-level clients.
• Media & Entertainment Domain Knowledge (Highly Preferred): Experience with broadcast and media workflows is a significant advantage. Familiarity with concepts like linear channel playout, live video streaming, media asset management (MAM), and IP video standards (e.g., SMPTE 2110) is highly desirable.
• Infrastructure as Code (IaC): Proficiency with IaC tools, particularly Terraform, for automating OCI environment provisioning.
• Professional Certifications: An OCI Architect Professional certification is strongly preferred. Equivalent certifications in AWS are also valued.

Job responsibilities

As the OCI Architect, you will be the primary technical authority and trusted advisor for this cloud migration initiative. Your responsibilities will include:

• Migration Strategy & Planning: Assess the client’s existing AWS-based media workflows and architect a comprehensive, phased migration strategy to OCI.
• Architecture Design: Design a secure, scalable, resilient, and cost-efficient OCI architecture tailored for demanding, 24/7 linear broadcast operations. This includes defining compute, storage, networking (including IP video transport), and security models.
• Technical Leadership: Serve as the subject matter expert on OCI for both the client and GlobalLogic engineering teams, providing hands-on guidance, best practices, and technical oversight.
• Stakeholder Engagement: Effectively communicate complex architectural concepts and migration plans to senior client stakeholders, technical teams, and project managers.
• Proof of Concept (PoC) Execution: Lead and participate in PoCs to validate architectural designs and de-risk critical components of the migration.
• Cost Optimization: Develop cost models and identify opportunities for optimizing operational expenses on OCI, ensuring the solution is commercially viable.
• Documentation: Create and maintain high-quality documentation, including architectural diagrams, design specifications, and operational runbooks.