Jobs Data Engineer

Core Responsibilities

 • Data Pipeline Management: Develop, optimize, and maintain scalable data pipelines to ensure high-quality data flow. 

• API Development: Build and maintain high-performance backend APIs using FastAPI. 

• System Reliability: Proactively identify bottlenecks and improve system stability within existing infrastructures.

 • Collaboration: Work closely with cross-functional teams to integrate AWS services and workflow orchestration tools into the production environment.

 

Required Qualifications 

• Experience: 3+ years of professional Python development experience. 

• Databases: Strong proficiency in both SQL and NoSQL database design and management. 

• DevOps Tools: Hands-on experience with Docker, CI/CD pipelines, and Git version control. 

• Frameworks: Proven experience building applications with FastAPI.

• Cloud & Orchestration: Practical experience with AWS services and familiarity with Airflow (or similar workflow orchestration tools). 

• Communication: Upper-Intermediate level of English (written and spoken) for effective team collaboration. 

 

 Preferred Skills (Nice to Have) 

• Experience within the Financial Domain. 

• Hands-on experience with Apache Spark and complex ETL pipelines.

• Knowledge of container orchestration using Kubernetes. 

• Exposure to or interest in Large Language Models (LLMs) and AI integration.

🔥 We’re looking for a highly skilled Data Expert!🔥

Product | Remote

About the role

We’re looking for an experienced Data Engineer to bring structure, reliability, and governance to our data ecosystem.

This is a hands-on, ownership-focused role where you will take full responsibility for ensuring that our data is consistent, trustworthy, and actionable.

Your main mission will be to stabilize and improve existing pipelines, enforce data standards, and maintain reliable datasets for analytics and business decisions. You’ll play a key role in shaping how teams trust and use data across the organization.

What you’ll do

• Build and maintain data pipelines and ETL processes
• Design and optimize data models for analytics and reporting
• Work with event-driven architectures and standards like AsyncAPI and CloudEvents
• Collaborate with engineers to improve data quality, consistency, and governance
• Use observability and tracing tools (e.g., OpenTelemetry) to monitor and improve performance
• Build and maintain datasets for analytics and reporting

You’re a great fit if you have 

• 5+ years of commercial experience, including 3+ years in data engineering
• Experience leading or significantly improving data governance processes
• Experience with data migrations in production
• Strong SQL and data modeling skills
• Familiarity with columnar or analytical databases (ClickHouse, Postgres, etc.)
• Understanding of observability, monitoring, and validation of data pipelines
• Ability to audit systems independently and identify weak spots
• Strong attention to detail and clear communication skills
• English proficiency: Upper-Intermediate or higher

Nice to have

• Exposure to BA tooling or visualization platforms
• Familiarity with Node.js / React / JavaScript / TypeScript 

How we’ll know you’re doing a great job

• Data pipelines are trusted, observable, and performant
• Metrics and dashboards are used across teams — not just built once
• Teams make better product decisions faster because of your insights
• Data pipelines are trusted, observable, and performant
• You’re the go-to person for clarity when questions arise about “what the data says”

About Redocly

Redocly builds tools that accelerate API ubiquity. Our platform helps teams create world-class developer experiences — from API documentation and catalogs to internal developer hubs and public showcases. We're a globally distributed team that values clarity, autonomy, and craftsmanship. You'll work alongside people who love developer experience, storytelling, and building tools that make technical work simpler and more joyful.

Headquarter – Austin, Texas, US. There is also an office in Lviv, Ukraine.

Redocly is trusted by leading tech, fintech, telecom, and enterprise teams to power API documentation and developer portals. Redocly’s clients range from startups to Fortune 500 enterprises.

https://redocly.com/

Working with Redocly

• Team: 4-6 people (middle-seniors)
• Team’s location: Ukraine&Europe
• There are functional, product, and platform teams and each has its own ownership, and line structure, and teams themselves decide when to have weekly meetings.
• Cross-functional teams are formed for each two-month cycle, giving team members the opportunity to work across all parts of the product.
• Methodology: Shape Up

Perks

• Competitive salary based on your expertise 
• Full remote, though you’re welcome to come to the office occasionally if you wish.
• Cooperation on a B2B basis with a US-based company (for EU citizens) or under a gig contract (for Ukraine).
• After a year of working with the company, you can buy a certain number of company’s shares
• Around 30 days of vacation (unlimited,  but let’s keep it reasonable)
• 10 working days of sick leave per year
• Public holidays according to the standards
• No trackers and screen recorders
• Working hours – EU/UA timezone. Working day – 8 hours. Mostly they start working from 10-11 am
• Equipment provided – MacBooks (M1 – M4)
• Regular performance reviews

Hiring Stages

• Prescreening (30-45 min)
• HR Call (45 min)
• Initial Interview (30 min)
• Trial Day (paid)
• Offer

If you are an experienced Data Scientist, and you want to work on impactful data-driven projects, we’d love to hear from you! 

Apply now to join our team!

We are a global audience and location intelligence company that helps marketers connect the digital and physical world. We provide data-driven solutions to enhance marketing campaigns by leveraging location and audience data to reveal consumer behavior and enable more precise targeting and measurement. We work on high-end / high-performance / high-throughput systems for in-time analysis of data for autonomous driving and other big data applications e.g. for E-commerce.


Job Description

You have 4+ years of experience on similar position.

You have significant experience with Python. Familiarity with Java or Scala is a plus.

Hands-on experience building scalable solutions in AWS.

Proficiency in NoSQL and SQL databases and in high-throughput data-related architecture and technologies (e.g. Kafka, Spark, Hadoop, MongoDB, AWS Batch, AWS Glue, Athena, Airflow, dbt).

Excellent SQL and data transformation skills.

Excellent written and verbal communication skills with an ability to simplify complex technical information.

Experience guiding and mentoring junior team members in a collaborative environment.


 

Job Responsibilities

Work in a self-organised agile team with a high level of autonomy, and you will actively shape your team's culture.

Design, build, and standardise privacy-first big data architectures, large-scale data pipelines, and advanced analytics solutions in AWS.

Develop complex integrations with third-party partners, transferring terabytes of data.

Align with other Data experts on data (analytics) engineering best practices and standards, and introduce those standards and data engineering expertise to the team in order to enhance existing data pipelines and build new ones.

Successfully partner up with the Product team to constantly develop further and improve our platform features.

Job Description

• Strong hands-on experience with Azure Databricks (DLT Pipelines, Lakeflow Connect, Delta Live Tables, Unity Catalog, Time Travel, Delta Share) for large-scale data processing and analytics
• Proficiency in data engineering with Apache Spark, using PySpark, Scala, or Java for data ingestion, transformation, and processing
• Proven expertise in the Azure data ecosystem: Databricks, ADLS Gen2, Azure SQL, Azure Blob Storage, Azure Key Vault, Azure Service Bus/Event Hub, Azure Functions, Azure Data Factory, and Azure CosmosDB
• Solid understanding of Lakehouse architecture, Modern Data Warehousing, and Delta Lake concepts
• Experience designing and maintaining config-driven ETL/ELT pipelines with support for Change Data Capture (CDC) and event/stream-based processing
• Proficiency with RDBMS (MS SQL, MySQL, PostgreSQL) and NoSQL databases
• Strong understanding of data modeling, schema design, and database performance optimization
• Practical experience working with various file formats, including JSON, Parquet, and ORC
• Familiarity with machine learning and AI integration within the data platform context
• Hands-on experience building and maintaining CI/CD pipelines (Azure DevOps, GitLab) and automating data workflow deployments
• Solid understanding of data governance, lineage, and cloud security (Unity Catalog, encryption, access control)
• Strong analytical and problem-solving skills with attention to detail
• Excellent teamwork and communication skills
• Upper-Intermediate English (spoken and written)
  
   

Job Responsibilities

• Design, implement, and optimize scalable and reliable data pipelines using Databricks, Spark, and Azure data services
• Develop and maintain config-driven ETL/ELT solutions for both batch and streaming data
• Ensure data governance, lineage, and compliance using Unity Catalog and Azure Key Vault
• Work with Delta tables, Delta Lake, and Lakehouse architecture to ensure efficient, reliable, and performant data processing
• Collaborate with developers, analysts, and data scientists to deliver trusted datasets for reporting, analytics, and machine learning use cases
• Integrate data pipelines with event-based and microservice architectures leveraging Service Bus, Event Hub, and Functions
• Design and maintain data models and schemas optimized for analytical and operational workloads
• Identify and resolve performance bottlenecks, ensuring cost efficiency and maintainability of data workflows
• Participate in architecture discussions, backlog refinement, estimation, and sprint planning
• Contribute to defining and maintaining best practices, coding standards, and quality guidelines for data engineering
• Perform code reviews, provide technical mentorship, and foster knowledge sharing within the team
• Continuously evaluate and enhance data engineering tools, frameworks, and processes in the Azure environment

Department/Project Description

GlobalLogic is searching for a motivated, results-driven, and innovative software engineer to join our project team at a dynamic startup specializing in pet insurance. Our client is a leading global holding company that is dedicated to developing an advanced pet insurance claims clearing solution designed to expedite and simplify the veterinary invoice reimbursement process for pet owners.
You will be working on a cutting-edge system built from scratch, leveraging Azure cloud services and adopting a low-code paradigm. The project adheres to industry best practices in quality assurance and project management, aiming to deliver exceptional results.
We are looking for an engineer who thrives in collaborative, supportive environments and is passionate about making a meaningful impact on people's lives. If you are enthusiastic about building innovative solutions and contributing to a cause that matters, this role could be an excellent fit for you.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

PwC Poland’s Cloud & Digital team supports global cloud projects across Cloud Strategy, Migrations, Data Analytics, and DevOps. We help clients adopt cloud infrastructure, modernize data platforms, and optimize operations. This hybrid role is based in Warsaw with flexible working options.

Your future role:

• Building data platforms (data warehouses, lakes, lakehouses) using Azure Databricks, MS Fabric, Azure Data Factory.
• Designing data flows using medallion architecture and supporting data migrations from legacy systems.
• Conducting data assessments with Data Modelers/Analysts and addressing data quality issues.
• Working with senior stakeholders to gather requirements and support modern data architecture design.
• Supporting Data Governance activities, especially around MDM and Data Quality.
• Understanding Data Science/Analytics use cases in industries like Consumer Goods, Retail, Manufacturing, or Financial Services.

Apply if you have:

• ~3 years of experience in Data Engineering or related fields (BI, Data Science).
• Hands‑on experience with Databricks, Snowflake, BigQuery, MS Fabric.
• Experience building data warehouses/lakehouses with Azure Data Factory / Synapse.
• Skills in PySpark/Python and SQL.
• Some exposure to CI/CD (Azure DevOps, Jira).
• B2+ English and ability to prepare technical documentation.
• Experience using modern tech and AI tools in daily work.

Nice to have:

• Cloud certifications (Azure/AWS/GCP) and Data Governance certifications.
• Training via platforms like Coursera/Udemy/Datacamp.
• Knowledge of data modelling (e.g., Kimball), Data Strategy, Data Quality, and MDM.
• Experience with Agile (Scrum), ML/GenAI use cases, or Agentic AI for data automation.
• Work with senior stakeholders (e.g., CDOs) in Manufacturing, Consumer Goods, or Financial Services.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

Department/Project Description

Client is a privately held medical device company headquartered in USA, specializing in non‑opioid, minimally invasive pain management solutions. The company is best known for its System, a short‑term 60‑day treatment designed to provide long‑lasting relief without surgery or permanent implants. Backed by the largest body of clinical evidence in peripheral nerve stimulation, cleint serves patients suffering from chronic pain conditions such as low back pain, post‑surgical pain, and neuropathic pain.

The client is in need to implement Data lake and integrate it with Salesforce Health Cloud.

You will work on a healthcare technology platform where mobile and backend software directly support a medical device used to treat pain in real-world clinical settings. The system already has active users and production constraints, and the focus of the project is to strengthen its technical foundation, improve reliability, and fix critical user-facing issues that affect authentication, session stability, notifications, and accessibility.




Job Description

In initial 2 months: Create a roadmap for next 1-2 year implementation

Work with key stakeholders and present the recommended solution for the client to be implemented.

After that:

End-to-End Solution Design:
• Design scalable, secure, and future-proof Salesforce solutions across Health cloud

Ensure designs align with platform limits, best practices, and enterprise guardrails.

After initial 2 months if approved by the client:

• Create robust data models, sharing models, role hierarchy designs, and scalable permission strategies.
• Guide teams on Case management and Workflow automation, Health Data Integration with Data lake

Closely cooperate with Date lake team to build an integrated solution for diagnostic tools, existing weareble device and patiant's data
• Own HLDs, LLDs, ERDs, integration specs, and data dictionaries.
• Maintain architectural runway and platform roadmap.

Job Responsibilities

Solution Design & Architecture

Design comprehensive, scalable, and secure Salesforce solutions across health cloud and connected systems.
Ensure all designs comply with Salesforce platform limits, enterprise standards, and best practices.
Maintain architectural runway and contribute to the long-term platform roadmap.

Data & Security Modeling

Develop robust data models, sharing models, and role hierarchy structures.
Implement scalable permission strategies aligned with business needs.

 

Documentation & Specifications

Own and deliver High-Level Designs (HLDs), Low-Level Designs (LLDs), Entity Relationship Diagrams (ERDs),  integration specifications, and data dictionaries.
Provide clear technical documentation for development and integration teams.

Integration & Governance

Define integration patterns and specifications for connected systems.
Ensure compliance with data governance and security standards.

Collaboration & Guidance

Partner with stakeholders, developers, and admins to ensure solution feasibility and alignment.
Act as a trusted advisor for Salesforce architecture and platform capabilities.

Build the data backbone for scalable analytics

Softsich is a young and ambitious international product tech company that develops scalable B2B digital platforms. We’re on the lookout for an experienced Senior Data Engineer who’s ready to grow with us and shape high-load, data-driven solutions used by international partners.

In this role, you will expand and maintain our AWS-based data warehouse, design analytical data models, and build reliable data pipelines that power reporting and business intelligence. If you enjoy working with modern data infrastructure, optimizing pipelines, and collaborating closely with analysts and product teams — this role may be a great match.

Your key responsibilities will include:

– Extend and maintain the existing AWS-based data warehouse by expanding the dbt infrastructure and developing new transformation models using SQL and dbt.
– Design and optimize analytical data models in Amazon Redshift to support reporting and business intelligence use cases.
– Develop and maintain data pipelines orchestrated in Amazon MWAA (Airflow) using Python-based DAGs.
– Migrate existing data pipelines from AWS Glue to MWAA to improve orchestration, maintainability, and scalability.
– Build data ingestion and transformation workflows that process data from multiple sources such as Kafka, MongoDB, and PostgreSQL.
– Implement data validation and verification scripts using Python, pandas, and numpy to ensure data quality and reliability.
– Collaborate with analysts and product owners to deliver well-structured datasets and ensure data integrity, performance, and accessibility.

It’s a match if you have:

– 3+ years of experience in data engineering or related roles.
– Strong understanding of data warehousing concepts, ETL/ELT processes, and data transformation techniques (MWAA preferred).
– Hands-on experience with data ingestion and processing using Kafka.
– Proficiency in SQL and experience with relational and NoSQL databases such as PostgreSQL and MongoDB.
– Experience with Python programming for data processing, automation, and pipeline development.
– Ability to work independently, take ownership of data systems, and collaborate effectively with analysts and product owners.
– Excellent communication and collaboration skills.

What we offer:

– Flexible schedule and remote format or offices in Warsaw/Kyiv — you choose.
– 24 paid vacation days, sick leaves, and health insurance (UA-based, other locations in progress).
– A supportive, friendly team where knowledge-sharing is part of the culture.
– Coverage for professional events and learning.
– Birthday greetings, team buildings, and warm human connection beyond work.
– Zero joules of energy to the aggressor state, its affiliated businesses, or partners.

Send over your CV now — we’d love to get to know you better!

Description

GlobalLogic is searching for a motivated, results-driven, and innovative software engineer to join our project team at a dynamic startup specializing in pet insurance. Our client is a leading global holding company that is dedicated to developing an advanced pet insurance claims clearing solution designed to expedite and simplify the veterinary invoice reimbursement process for pet owners.
You will be working on a cutting-edge system built from scratch, leveraging Azure cloud services and adopting a low-code paradigm. The project adheres to industry best practices in quality assurance and project management, aiming to deliver exceptional results.
We are looking for an engineer who thrives in collaborative, supportive environments and is passionate about making a meaningful impact on people’s lives. If you are enthusiastic about building innovative solutions and contributing to a cause that matters, this role could be an excellent fit for you.

Requirements

• Strong hands-on experience with Azure Databricks (DLT Pipelines, Lakeflow Connect, Delta Live Tables, Unity Catalog, Time Travel, Delta Share) for large-scale data processing and analytics
• Proficiency in data engineering with Apache Spark, using PySpark, Scala, or Java for data ingestion, transformation, and processing
• Proven expertise in the Azure data ecosystem: Databricks, ADLS Gen2, Azure SQL, Azure Blob Storage, Azure Key Vault, Azure Service Bus/Event Hub, Azure Functions, Azure Data Factory, and Azure CosmosDB
• Solid understanding of Lakehouse architecture, Modern Data Warehousing, and Delta Lake concepts
• Experience designing and maintaining config-driven ETL/ELT pipelines with support for Change Data Capture (CDC) and event/stream-based processing
• Proficiency with RDBMS (MS SQL, MySQL, PostgreSQL) and NoSQL databases
• Strong understanding of data modeling, schema design, and database performance optimization
• Practical experience working with various file formats, including JSON, Parquet, and ORC
• Familiarity with machine learning and AI integration within the data platform context
• Hands-on experience building and maintaining CI/CD pipelines (Azure DevOps, GitLab) and automating data workflow deployments
• Solid understanding of data governance, lineage, and cloud security (Unity Catalog, encryption, access control)
• Strong analytical and problem-solving skills with attention to detail
• Excellent teamwork and communication skills
• Upper-Intermediate English (spoken and written)

Job responsibilities

• Design, implement, and optimize scalable and reliable data pipelines using Databricks, Spark, and Azure data services
• Develop and maintain config-driven ETL/ELT solutions for both batch and streaming data
• Ensure data governance, lineage, and compliance using Unity Catalog and Azure Key Vault
• Work with Delta tables, Delta Lake, and Lakehouse architecture to ensure efficient, reliable, and performant data processing
• Collaborate with developers, analysts, and data scientists to deliver trusted datasets for reporting, analytics, and machine learning use cases
• Integrate data pipelines with event-based and microservice architectures leveraging Service Bus, Event Hub, and Functions
• Design and maintain data models and schemas optimized for analytical and operational workloads
• Identify and resolve performance bottlenecks, ensuring cost efficiency and maintainability of data workflows
• Participate in architecture discussions, backlog refinement, estimation, and sprint planning
• Contribute to defining and maintaining best practices, coding standards, and quality guidelines for data engineering
• Perform code reviews, provide technical mentorship, and foster knowledge sharing within the team
• Continuously evaluate and enhance data engineering tools, frameworks, and processes in the Azure environment

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About Pulse Intelligence

Pulse Intelligence is building the definitive data platform for the global mining industry. We aggregate, process, and enrich data from hundreds of sources (regulatory filings, stock exchanges, company websites, news, and financial APIs) to give mining investors and analysts a real-time, comprehensive view of every mining asset, company, and commodity on the planet.

Our platform combines large-scale web scraping with LLM-powered data extraction to turn unstructured documents (NI 43-101 technical reports, RNS announcements, SEDAR filings) into structured, queryable intelligence. We're a small team shipping fast, and every engineer has an outsized impact on the product.

About the Role

We're looking for a Senior AI Data Engineer to take ownership of our entire data pipeline, from raw document ingestion through AI-powered extraction to clean, structured records in our database. You'll be the technical lead on data acquisition and enrichment: architecting scrapers for new sources, designing LLM extraction strategies, making decisions on data modeling, and driving the quality and coverage of our mining asset database.

This is a high-autonomy role for someone who can see the big picture and execute on the details. You'll decide which data sources to prioritise, how to structure extraction pipelines, and when to invest in automation vs. manual curation. You'll ship scrapers one day, redesign an entity extraction pipeline the next, and mentor the team on best practices throughout.

What You'll Do

• Own data acquisition and scraping - identify, prioritise, and build scrapers for new data sources (exchanges, regulatory filings, company websites, financial APIs) and scale them to run reliably in production
• Design LLM extraction pipelines - architect and iterate on prompt-driven pipelines that extract structured mining data (assets, production, reserves, companies) from unstructured documents
• Build the document processing pipeline - take raw PDFs, HTML, and filings from ingestion through to clean, structured data using OCR, parsing, deduplication, and text normalisation
• Drive data quality and coverage - design verification, deduplication, and enrichment workflows, and own the data model that keeps our mining asset database accurate and well-structured
• Keep pipelines running - monitor scheduled jobs, design for failure recovery, and ensure the system scales without manual intervention

What You Need

• 5+ years of Python in data engineering or backend development
• Web scraping at scale - you've built and maintained production scrapers (Scrapy, Playwright, Selenium, or similar)
• Prompt engineering - you've used LLM APIs (OpenAI, Anthropic, or similar) to extract structured data from unstructured text, and you iterate on prompts systematically
• Strong SQL and data modeling - you've designed schemas and optimised queries in PostgreSQL or similar
• Self-directed - you identify what needs doing and drive it to completion with minimal oversight

Nice to Haves

• Mining or resources industry knowledge (NI 43-101, JORC, resource classifications)
• AWS (S3, EKS) or similar cloud infrastructure
• LLM self-verification, chain-of-thought, or agentic pipelines
• Experience with workflow orchestration tools (Airflow, Dagster, or similar)
• Experience mentoring engineers or leading a small data team

Benefits

• Work on a product that maps the entire global mining industry
• Small team - your work directly shapes the product
• Remote-friendly with flexible hours
• Equity in a growing platform

Hiring Process

• Introductory call - 30 minutes
• Take-home challenge - 6 hours
• Technical & cultural fit interview - 1 hour
• System design interview - 1 hour

We are looking for you!
 

As we continue to design and build data-driven solutions across diverse domains — we’re seeking a Data Engineer who thrives on transforming data into impactful insights. If you’re passionate about crafting robust architectures, optimizing data pipelines, and enabling intelligent decision-making at scale, we’d love to have you join our global team and shape the next generation of data excellence with us.

Contract type: Gig contract.

Skills and experience you can bring to this role
 

Qualifications & experience:
 

• 5+ years of intensive experience as a Data Engineer or in a similar role, with a demonstrable track record of leading large-scale projects;
• Mastery in Python and data stack (NumPy, Pandas, scikit-learn);
• Good Understanding of SQL/RDBMS and familiarity with data warehouses (BigQuery, Snowflake, Redshift, etc.);
• Experience building ETL data pipelines (Airflow, Prefect, Dagster, etc);
• Experience with modern Scrum-based Software Development Life Cycle (SDLC);
• Strong communication skills to explain technical insights to non-technical stakeholders.

Nice to have:

• Hands-on experience with Python web stack (Fast API / Flask);
• Proven expertise in designing and optimizing large-scale data pipelines;
• Comprehensive understanding of data governance principles and data quality management practices;
• Understand marketing and media metrics (i.e., what conversion rate is and how it is calculated).
• Exceptional leadership, communication, and collaboration skills, with a knack for guiding and nurturing teams.
   

Educational requirements:

• Bachelor’s degree in Computer Science, Information Systems, or a related discipline is preferred.

What impact you’ll make 
 

• Lead the design, development, testing, and maintenance of scalable data architectures, ensuring they align with business and technical objectives;
• Spearhead the creation of sophisticated data pipelines using Python, leveraging advanced Snowflake capabilities such as Data Shares, Snowpipe, Snowpark, and more;
• Collaborate intensively with data scientists, product teams, and other stakeholders to define and fulfill intricate data requirements for cross-channel budget optimization solutions;
• Drive initiatives for new data collection, refining existing data sources, and ensuring the highest standards of data accuracy and reliability;
• Set the gold standard for data quality, introducing cutting-edge tools and frameworks to detect and address data inconsistencies and inaccuracies; and
• Identify, design, and implement process improvements, focusing on data delivery optimization, automation of manual processes, and infrastructure enhancements for scalability.

What you’ll get 
 

Regardless of your position or role, we have a wide array of benefits in place, including flexible working (hybrid/remote models) and generous time off policies (unlimited vacations, sick and parental leaves) to make it easier for all people to thrive and succeed at Star. On top of that, we offer an extensive reward and compensation package, intellectually and creatively stimulating space, health insurance and unique travel opportunities.

Your holistic well-being is central at Star. You'll join a warm and vibrant multinational environment filled with impactful projects, career development opportunities, mentorship and training programs, fun sports activities, workshops, networking and outdoor meet-ups.

Description

About project: Mobile marketing and audience platform
 

Leading mobile marketing and audience platform, empowers the app ecosystem with cutting-edge solutions in mobile marketing, audience building, and monetization. With integration into over 500,000 monthly active apps and a global reach, our team leverages first-party data to deliver impactful and scalable advertising solutions.
 

We’re looking for a highly skilled, independent, and driven Machine Learning Engineer to lead the design and development of our next-generation real-time inference services - the core engine powering algorithmic decision-making at scale. This is a rare opportunity to own the system at the heart of our product, serving billions of daily requests across mobile apps, with tight latency and performance constraints.
 

Our platform empowers the mobile app ecosystem, simplifying mobile marketing, audience building, and mobile monetization. With direct integration into over 500,000 mobile apps, our platform processes enormous volumes of first-party data to drive intelligent, real-time decisions that fuel growth for our partners.
 

You’ll work at the intersection of machine learning, large-scale backend engineering, and business logic, building robust services that blend predictive models with dynamic, engineering logic - all while maintaining extreme performance and reliability requirements.

Job Description:
 

· Own and lead the design and development of low-latency Algo inference services handling billions of requests per day

· Build and scale robust real-time decision-making engines, integrating ML models with business logic under strict SLAs

· Collaborate closely with DS to deploy models seamlessly and reliably in production

· Design systems for model versioning, shadowing, and A/B testing at runtime

· Ensure high availability, scalability, and observability of production systems

· Continuously optimize latency, throughput, and cost-efficiency using modern tooling and techniques

· Work independently while interfacing with cross-functional stakeholders from Algo, Infra, Product, Engineering, BA & Business.
 

Requirements
 

· 5+ years of experience building high-performance backend or ML inference systems

· Deep expertise in Python and experience with low-latency APIs and real-time serving frameworks (e.g., FastAPI, Triton Inference Server, TorchServe, BentoML)
· B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related technical discipline

· Experience with scalable service architecture, message queues (Kafka, Pub/Sub), and async processing

· Strong understanding of model deployment practices, online/offline feature parity, and real-time monitoring

· Experience in cloud environments (AWS, GCP, or OCI) and container orchestration (Kubernetes)

· Experience working with in-memory and NoSQL databases (e.g. Aerospike, Redis, Bigtable) to support ultra-fast data access in production-grade ML services

· Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry) and best practices for alerting and diagnostics

· A strong sense of ownership and the ability to drive solutions end-to-end

· Passion for performance, clean architecture, and impactful systems

Interview process: 2-3 stages (technical/test task and interpersonal + HR).

Job Description

• Strong hands-on experience with Azure Databricks (DLT Pipelines, Lakeflow Connect, Delta Live Tables, Unity Catalog, Time Travel, Delta Share) for large-scale data processing and analytics
• Proficiency in data engineering with Apache Spark, using PySpark, Scala, or Java for data ingestion, transformation, and processing
• Proven expertise in the Azure data ecosystem: Databricks, ADLS Gen2, Azure SQL, Azure Blob Storage, Azure Key Vault, Azure Service Bus/Event Hub, Azure Functions, Azure Data Factory, and Azure CosmosDB
• Solid understanding of Lakehouse architecture, Modern Data Warehousing, and Delta Lake concepts
• Experience designing and maintaining config-driven ETL/ELT pipelines with support for Change Data Capture (CDC) and event/stream-based processing
• Proficiency with RDBMS (MS SQL, MySQL, PostgreSQL) and NoSQL databases
• Strong understanding of data modeling, schema design, and database performance optimization
• Practical experience working with various file formats, including JSON, Parquet, and ORC
• Familiarity with machine learning and AI integration within the data platform context
• Hands-on experience building and maintaining CI/CD pipelines (Azure DevOps, GitLab) and automating data workflow deployments
• Solid understanding of data governance, lineage, and cloud security (Unity Catalog, encryption, access control)
• Strong analytical and problem-solving skills with attention to detail
• Excellent teamwork and communication skills
• Upper-Intermediate English (spoken and written)

Job Responsibilities

• Design, implement, and optimize scalable and reliable data pipelines using Databricks, Spark, and Azure data services
• Develop and maintain config-driven ETL/ELT solutions for both batch and streaming data
• Ensure data governance, lineage, and compliance using Unity Catalog and Azure Key Vault
• Work with Delta tables, Delta Lake, and Lakehouse architecture to ensure efficient, reliable, and performant data processing
• Collaborate with developers, analysts, and data scientists to deliver trusted datasets for reporting, analytics, and machine learning use cases
• Integrate data pipelines with event-based and microservice architectures leveraging Service Bus, Event Hub, and Functions
• Design and maintain data models and schemas optimized for analytical and operational workloads
• Identify and resolve performance bottlenecks, ensuring cost efficiency and maintainability of data workflows
• Participate in architecture discussions, backlog refinement, estimation, and sprint planning
• Contribute to defining and maintaining best practices, coding standards, and quality guidelines for data engineering
• Perform code reviews, provide technical mentorship, and foster knowledge sharing within the team
• Continuously evaluate and enhance data engineering tools, frameworks, and processes in the Azure environment

Department/Project Description

GlobalLogic is searching for a motivated, results-driven, and innovative software engineer to join our project team at a dynamic startup specializing in pet insurance. Our client is a leading global holding company that is dedicated to developing an advanced pet insurance claims clearing solution designed to expedite and simplify the veterinary invoice reimbursement process for pet owners.
You will be working on a cutting-edge system built from scratch, leveraging Azure cloud services and adopting a low-code paradigm. The project adheres to industry best practices in quality assurance and project management, aiming to deliver exceptional results.
We are looking for an engineer who thrives in collaborative, supportive environments and is passionate about making a meaningful impact on people's lives. If you are enthusiastic about building innovative solutions and contributing to a cause that matters, this role could be an excellent fit for you.

About Sembly AI

Sembly AI is a SaaS platform that transforms conversations into actionable intelligence. We are a product-led company with thousands of daily users. Our technology integrates with Zoom, Microsoft Teams, Google Meet, and Webex to generate polished deliverables (summaries, reports, proposals) and actionable insights.

About the role

We are hiring a Marketing Data Engineer to build and maintain the data infrastructure that powers marketing analytics and campaign decision-making at Sembly.

This role focuses on aggregating and structuring data from multiple systems including web analytics, CRM, advertising platforms, and product usage data. The goal is to create reliable datasets and dashboards that help the marketing team evaluate campaign performance and allocate budget effectively.

You will work closely with the Head of Growth Marketing to ensure that metrics such as CAC, ROAS, funnel performance, and campaign attribution are accurately measured and clearly surfaced through dashboards and reporting tools.

This is a technical role focused on data integration, modeling, and visualization, not campaign execution.

Responsibilities

• Aggregate and integrate data from multiple sources including:
  • Google Analytics
  • CRM systems
  • Ad platforms (Google Ads, LinkedIn Ads, etc.)
  • Product usage and user event data
• Build and maintain data pipelines that consolidate marketing data into unified datasets
• Develop data models that support marketing performance analysis
• Design and maintain dashboards and reporting systems for campaign performance
• Surface key metrics including:
  • CAC
  • ROAS
  • Funnel conversion metrics
  • Campaign performance across channels
• Develop attribution views across marketing channels
• Identify inconsistencies or gaps in tracking and implement solutions
• Support marketing decision-making by producing reliable datasets and insights
• Continuously improve the marketing data infrastructure as new campaigns and channels are introduced
• Design, run, and analyze A/B tests to optimize website conversion rates and improve the customer onboarding journey
• Support the Growth Marketing team in day-to-day channel operations and ongoing optimisation activities

Skills & experience

• 3+ years of experience in data engineering, analytics engineering, or marketing data roles
• Strong Python experience for data ingestion, transformation, and automation
• Strong understanding of SQL for querying and transforming structured datasets
• Experience building ETL / ELT pipelines and scheduled data workflows
• Familiarity with databases or data warehouses (eg, PostgreSQL)
• Experience with data visualization tools such as Grafana, Mixpanel, Metabase, Looker, or similar
• Strong attention to data quality, consistency, and validation
• Ability to synthesize complex marketing and performance data into clear, actionable insights to optimize channel performance and inform strategic decision-making
• Familiarity with A/B testing and experimentation tools

Nice to haves

• Experience working with event-based product analytics data (user events, funnels, cohorts)
• Understanding of marketing attribution and campaign performance metrics (CAC, ROAS, funnel conversion metrics)
• Experience integrating advertising platform data (Google Ads, LinkedIn Ads)
• Technical knowledge of key performance marketing channels, including paid platforms such as Google Ads, as well as organic channels including SEO and social media.
• Experience using AI-assisted coding tools (e.g., Cursor, Codex) to accelerate development

Why join our team

• High-impact technical role supporting core marketing decision-making
• Collaborative and supporting team with direct access to leadership
• Opportunity to build a clean marketing data infrastructure from the ground up
• AI-friendly team that welcomes cutting edge tools and AI-powered solutions
• Flexible remote-first work environment

We are looking for a Data Engineer to join our team!

Data Engineer is responsible for designing, maintaining, and optimizing data infrastructure for data collection, management, transformation, and access.

He/she will be in charge of creating pipelines that convert raw data into usable formats for data scientists and other data consumers to utilize.

Data Engineer should be comfortable working with RDBMS and has a good knowledge of the appropriate RDBMS programming language(s) as well.

The Data Engineer fulfills processing of client data based on proper specification and documentation.

     Main responsibilities:

• Design and develop ETL pipelines;
• Data integration and cleansing;
• Implement stored procedures and function for data transformations;
• ETL processes performance optimization.

     Skills and Requirements:

• Experience with ETL tools (to take charge of the ETL processes and performs tasks connected with data analytics, data science, business intelligence and system architecture skills);
• Database/DBA/Architect background (understanding of data storage requirements and design warehouse architecture, should have the basic expertise with SQL/NoSQL databases and data mapping, the awareness of Hadoop environment);
• Data analysis expertise (data modeling, mapping, and formatting, data analysis basic expertise is required);
• Knowledge of scripting languages (Python is preferable);
• Troubleshooting skills (data processing systems operate with large amounts of data and include multiple structural elements. Data Engineer is responsible for the proper functioning of the system, which requires strong analytical thinking and troubleshooting skills);
• Tableau experience is good to have;
• Software engineering background is good to have;
• Good organizational skills, and task management abilities;
• Effective self-motivator;
• Good communication skills in written and spoken English.

     Salary Range

Compensation packages are based on several factors including but not limited to: skill set, depth of experience, certifications, and specific work location.

Are you passionate about building large-scale cloud data infrastructure that makes a real difference? We are looking for a Senior Data Engineer to join our team and work on an impactful healthcare technology project. This role offers a remote work format with the flexibility to collaborate across international teams.

At Sigma Software, we deliver innovative IT solutions to global clients in multiple industries, and we take pride in projects that improve lives. Joining us means working with cutting-edge technologies, contributing to meaningful initiatives, and growing in a supportive environment.

CUSTOMER
Our client is a leading medical technology company. Its portfolio of products, services, and solutions is at the center of clinical decision-making and treatment pathways. Patient-centered innovation has always been, and will always be, at the core of the company. The client is committed to improving patient outcomes and experiences, regardless of where patients live or what they face. The Customer is innovating sustainably to provide healthcare for everyone, everywhere. 

PROJECT
The project focuses on building and maintaining large-scale cloud-based data infrastructure for healthcare applications. It involves designing efficient data pipelines, creating self-service tools, and implementing microservices to simplify complex processes. The work will directly impact how healthcare providers access, process, and analyze critical medical data, ultimately improving patient care.

Responsibilities:

• Collaborate with the Product Owner and team leads to define and design efficient pipelines and data schemas
• Build and maintain infrastructure using Terraform for cloud platforms
• Design and implement large-scale cloud data infrastructure, self-service tooling, and microservices
• Work with large datasets to optimize performance and ensure seamless data integration
• Develop and maintain squad-specific data architectures and pipelines following ETL and Data Lake principles
• Discover, analyze, and organize disparate data sources into clean, understandable schemas

Requirements:

• Possibility to meet clients annually in Europe
• Hands-on experience with cloud computing services in data and analytics
• Experience with data modeling, reporting tools, data governance, and data warehousing
• Proficiency in Python and PySpark for distributed data processing
• Experience with Azure, Snowflake, and Databricks
• Experience with Docker and Kubernetes
• Knowledge of infrastructure as code (Terraform)
• Advanced SQL skills and familiarity with big data databases such as Snowflake, Redshift, etc.
• Experience with stream processing technologies such as Kafka, Spark Structured Streaming
• At least an Upper-Intermediate level of English 

Чи захоплюєтесь ви створенням масштабної хмарної інфраструктури даних, яка має реальний вплив? Ми шукаємо Senior Data Engineer, який приєднається до нашої команди та працюватиме над важливим проєктом у сфері медичних технологій. Ця роль передбачає віддалений формат роботи з можливістю співпрацювати з міжнародними командами.

У Sigma Software ми створюємо інноваційні ІТ-рішення для глобальних клієнтів у різних галузях і пишаємося проєктами, які покращують життя людей. Приєднавшись до нас, ви працюватимете з передовими технологіями, робитимете внесок у значущі ініціативи та розвиватиметеся в підтримуючому середовищі.

Клієнт:
Наш клієнт — провідна компанія у сфері медичних технологій. Її портфель продуктів, сервісів та рішень знаходиться в центрі процесів клінічного прийняття рішень і побудови шляхів лікування. Інновації, орієнтовані на пацієнтів, завжди були і залишаються основою діяльності компанії. Клієнт прагне покращувати результати лікування та досвід пацієнтів незалежно від того, де вони живуть і з якими викликами стикаються. Компанія інноваційно розвивається, щоб забезпечити доступ до медицини для кожного, всюди.

Проєкт:
Проєкт зосереджений на створенні та підтримці масштабної хмарної інфраструктури даних для медичних застосунків. Він включає проєктування ефективних data pipelines, створення self-service інструментів та реалізацію мікросервісів для спрощення складних процесів. Робота безпосередньо впливатиме на те, як медичні установи отримують доступ до критично важливих медичних даних, обробляють їх та аналізують, що зрештою покращує якість медичної допомоги пацієнтам.

 

Обов'язки: 

• Співпрацювати з Product Owner та технічними лідами для визначення та проєктування ефективних pipelines і схем даних
• Будувати та підтримувати інфраструктуру для хмарних платформ за допомогою Terraform
• Проєктувати та впроваджувати масштабну хмарну інфраструктуру даних, self-service інструменти та мікросервіси
• Працювати з великими наборами даних для оптимізації продуктивності та забезпечення безперебійної інтеграції даних
• Розробляти та підтримувати архітектури даних і pipelines для команди відповідно до принципів ETL та Data Lake
• Виявляти, аналізувати та впорядковувати різнорідні джерела даних у зрозумілі та чисті схеми

Вимоги:

• Можливість раз на рік зустрічатися з клієнтами в Європі
• Практичний досвід роботи з хмарними сервісами для даних та аналітики
• Досвід data modeling, reporting tools, data governance та data warehousing
• Впевнене володіння Python і PySpark для розподіленої обробки даних
• Досвід роботи з Azure, Snowflake та Databricks
• Досвід роботи з Docker та Kubernetes
• Знання infrastructure as code (Terraform)
• Просунуті навички SQL та знайомство з big data базами даних, такими як Snowflake, Redshift тощо
• Досвід роботи зі stream processing технологіями, такими як Kafka, Spark Structured Streaming
• Рівень англійської не нижче Upper-Intermediate