Jobs Data Engineer

We are looking for an experienced Senior Data Scientist to join our team and help unlock the full value of data across our platform, products, and business operations. In this role, you will apply advanced analytics, machine learning, and statistical modeling to generate actionable insights, improve decision-making, and drive innovation across the organization.

Responsibilities

• Analyze large, complex datasets to uncover trends, patterns, and insights that support strategic business and product decisions.
• Build predictive models to forecast business outcomes, improve operational efficiency, and support decision-making across multiple functions.
• Design and implement feature engineering techniques to improve machine learning model performance and accuracy.
• Partner with cross-functional teams including product, engineering, operations, and business stakeholders to identify opportunities and translate them into scalable data science solutions.
• Clean, preprocess, and structure data from multiple sources to ensure high-quality inputs for analysis and modeling.
• Develop, test, and deploy machine learning models for use cases such as classification, regression, clustering, recommendation systems, and forecasting.
• Evaluate and optimize model performance using appropriate statistical and machine learning metrics.
• Create dashboards, reports, and visualizations that clearly communicate findings and recommendations to technical and non-technical audiences.
• Automate recurring analysis, reporting, and model workflows to improve efficiency and consistency.
• Monitor production models and continuously improve performance, reliability, and business impact over time.
• Stay current with the latest advancements in data science, machine learning, and AI, and apply relevant innovations to PredictSpring’s platform and operations.

Requirements

• Excellent communication skills, including fluent verbal English, with the ability to explain complex concepts to non-technical stakeholders and collaborate effectively across teams.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Proven experience as a Data Scientist, with a strong background in machine learning, statistical analysis, and predictive modeling.
• Strong programming skills in Python preferred, or similar languages such as R, with hands-on experience using libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Expertise in building and deploying machine learning models for classification, regression, time-series forecasting, recommendation systems, and related applications.
• Strong experience with data wrangling, feature engineering, and working with structured and unstructured datasets.
• Proficiency in SQL for querying, transforming, and analyzing structured data.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for model deployment and data workflows.
• Experience with data visualization tools such as Power BI, Tableau, or Python visualization libraries.
• Strong analytical thinking, problem-solving ability, and a passion for applying data science to real-world business challenges.

Preferred Qualifications

• Familiarity with big data and distributed processing tools such as Apache Spark, Hadoop, or Databricks.
• Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Experience with natural language processing techniques such as text classification, sentiment analysis, or large language model applications.
• Strong foundation in statistical analysis, experimentation, and hypothesis testing.
• Experience collaborating with or supporting data engineering teams in building scalable data pipelines.
• Familiarity with version control tools such as Git.
• Strong business acumen and the ability to align technical solutions with business goals.
• Experience in retail, e-commerce, omni-channel commerce, or POS technology is a strong plus.

Why PredictSpring?

• Join a market-leading company shaping the future of omni-channel retail and modern POS.
• Work on high-impact challenges at the intersection of commerce, data, and customer experience.
• Collaborate with a talented global team in a flexible remote work environment.
• Enjoy opportunities for growth, learning, and professional development.
• Contribute to products used by some of the world’s most recognized retail and lifestyle brands.
• Be part of an innovative, collaborative, and data-driven culture focused on delivering measurable business value.

Data is at the core of every product decision we make. In this role, you’ll help shape and scale the data ecosystem behind products used by millions of users across international markets. You’ll work on high-volume data platforms, build reliable pipelines, and create the foundation that enables analytics, business intelligence, and data science teams to make fast, data-driven decisions. This is an opportunity to solve complex engineering challenges, optimize large-scale data systems, and directly influence the way data powers our products and business growth

In this role, you will
 

• Design and develop scalable, cloud-native data architectures in BigQuery, ensuring optimal performance, maintainability, and cost efficiency
• Build, automate, and maintain ETL/ELT pipelines using modern data stack tools and custom solutions
• Create and optimize business-critical data marts, aggregations, and analytical datasets for reporting, dashboarding, and product insights
• Implement data quality frameworks, monitoring systems, logging, and alerting mechanisms to ensure data reliability
• Continuously improve performance, scalability, and cost efficiency of production data infrastructure
• Partner closely with Data Science teams to build reliable data services, infrastructure, and pipelines supporting machine learning and advanced analytics initiatives
• Collaborate with product, analytics, and engineering teams to define and deliver scalable data solutions across the organization
  
  It’s all about you
   
• 3+ years of experience as a Data Engineer working with large-scale data platforms and high-volume datasets
• Strong expertise in data modeling, data warehousing concepts, and analytical data architecture design
• Proven experience designing and developing complex ETL/ELT workflows following BI and data engineering best practices
• Hands-on experience with BigQuery, including partitioning, clustering, query optimization, and cost management
• Strong SQL skills with the ability to write and optimize complex analytical queries using Google SQL
• Proficiency in Python and data processing libraries such as Pandas and PySpark
• Experience working with ClickHouse, including architecture understanding, performance optimization, and migration approaches
• Solid knowledge of Google Cloud Platform services, including Cloud Storage, Pub/Sub, DataForm, IAM, and service accounts
• Experience with Git, CI/CD practices, automated deployments, and environment management for data workflows
• Strong understanding of monitoring, logging, data validation, and production-grade data quality practices
• Excellent analytical thinking, problem-solving skills, and ability to work independently in a fast-paced environment
• Strong communication and collaboration skills with both technical and non-technical stakeholders
• Understanding of product metrics, experimentation frameworks, and data-driven decision making
• 2+ years of previous Software Engineering experience
• Experience optimizing storage and compute resources to improve infrastructure efficiency and reduce operational costs
• Experience integrating data platforms with BI tools such as Tableau or Looker
  
  Would be a plus
   
• Familiarity with supporting machine learning workflows and data infrastructure for Data Science teams
• Experience working with AI-powered development tools, including Claude Code, Claude Agents, or similar AI-assisted engineering solutions
  
  What we offer
• Care and support: 
• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Maternity Recovery Support Allowance
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   
• Comfortable working environment:
• Work from our Kyiv hub or remotely with a flexible schedule 
• Modern equipment or depreciation of your own tools
  
  Investment in your future:
• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   
• Hiring process
• Intro call
• Technical interview
• Final  interview
• Reference check
• Offer
   

Start: asap
Duration: long-term
Location: any
English: B2

Summary
We are looking for a senior GCP Data Engineer / Data Architect to lead and execute an on-premise GCP data migration project.

This is a hands-on data-focused role, not a classic DevOps/Kubernetes role.

Main responsibilities:
* Lead and implement the migration of data workloads from on-premise infrastructure to GCP
* Design and build GCP data lake / lakehouse architecture
* Work hands-on with GCP data services such as BigQuery, Dataproc, Cloud Storage, Spark, and related tools
* Design and implement scalable data pipelines and data processing flows
* Handle data ingestion, storage, security, reliability, and cost optimization
* Work independently with the existing technical team and drive technical decisions

Required experience:
* Strong hands-on GCP data engineering experience
* BigQuery, Dataproc, Spark, and Cloud Storage
* Data lake / lakehouse architecture
* On-premise to cloud migration experience
* Ability to lead technical decisions and work independently

Nice to have:
* Terraform / Infrastructure as Code
* Dataflow, Pub/Sub, Cloud Composer / Airflow
* GCP IAM, networking, monitoring, and security

Full-time availability is preferred.
Please apply only if you have real hands-on experience with GCP data platforms and data migration projects.

Data Engineer / ETL Developer

Location: Remote

Duration: 3 months contract with potential for long-term extension
Budget: Up to $2800-3800/month (depends on your experience)
 

About the Role

We are looking for a Data Engineer / ETL Developer with 2–4 years of experience to support the migration of existing SSIS processes into a Microsoft Fabric environment. 
 

Responsibilities

• Migrate existing SSIS packages and ETL processes to Microsoft Fabric.
• Design, develop, and optimize ETL/ELT pipelines.
• Work closely with stakeholders to understand data integration requirements.
• Ensure data quality, reliability, and performance throughout the migration process.
• Troubleshoot and resolve data pipeline issues.
   

Requirements

• 2–4 years of experience as a Data Engineer, ETL Developer, or similar role.
• Strong experience with ETL development and data integration.
• Hands-on experience with SQL and relational databases.
• Experience working with SSIS (SQL Server Integration Services).
• Familiarity with Microsoft Fabric (preferred).
• Understanding of data warehousing concepts and best practices.
• Ability to work independently in a remote environment.
• Good communication skills in English.
   

Nice to Have

• Experience with Azure Data Services.
• Experience with cloud-based data platforms and migration projects.
• Knowledge of data modeling and performance optimization.
   

Engagement Details

• Fully remote.
• Initial 3-month engagement.
• Potential for long-term collaboration based on project needs and performance.

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.
We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client looking for a Platform Engineer to drive critical infrastructure initiatives across our backend systems, with primary ownership of our core platform.
This is a high-impact role where you'll architect scalable solutions that serve our entire engineering organization - core platform services that power our AI editing capabilities.
You'll have the opportunity to shape technical decisions across multiple domains while ensuring our platform systems are robust, reliable, and optimized for growth.

Key Requirements:
🔹 5+ years of experience as a Backend Engineer, with experience building platform services or shared infrastructure;
🔹 B.Sc in Computer Science, Software Engineering, or a related field from a well-known university;
🔹 Proven expertise in backend server development, using languages like Python, Scala, Go, or Java;
🔹 Solid understanding of system design principles, API architecture, and service-oriented architectures;
🔹 Proficiency with AWS services and cloud-based architectures;
🔹 Excellent communication skills for collaborating across engineering, product, and operations teams;
🔹 Proactive mindset, having the will and ability to find areas where optimizations can benefit the entire org;
🔹 English – Upper-Intermediate or higher.

What you will do:
🔹 Drive platform-level initiatives that improve scalability, reliability, and developer experience across our backend systems;
🔹 Collaborate with multiple departments to support new platform features and technical initiatives;
🔹 Monitor platform health, investigating and resolving incidents and reliability issues;
🔹 Develop and optimize shared platform services, APIs, and infrastructure used across engineering teams;
🔹 Create internal tools and frameworks that improve developer productivity and system reliability;
🔹 Drive initiatives to improve observability, monitoring, and operational excellence across our infrastructure;

Interview stages:
🔹 HR Interview;
🔹 Tech interview;
🔹 Client Interviews;
🔹 Reference check;
🔹 Offer;

Our client is a fast-growing SaaS company in the hospitality industry. Their platform helps leading hotel brands transform front-desk teams into revenue generators through upselling training, performance analytics, and data-driven insights.

Their flagship platform is used across 2,000+ hotel properties in more than 100 countries, helping hospitality teams improve guest experiences while increasing revenue.

We are looking for an experienced Data Engineer to join a growing data team and play a key role in building and scaling data infrastructure, pipelines, and analytics capabilities.

Requirements:

• 5+ years of commercial experience in Data Engineering.
• 3+ years of hands-on experience with AWS.
• 2+ years of experience with Spark/PySpark.
• Strong Python skills.
• Experience designing and maintaining ETL/ELT pipelines.
• Experience working with large-scale, high-load data environments.
• Solid understanding of data warehousing concepts and best practices.
• Ability to work independently and take ownership of solutions.
• Proactive mindset and strong problem-solving skills.
• English C1.

Nice to Have:

• Experience with modern data orchestration tools.
• Experience with real-time data processing.
• Knowledge of CI/CD practices for data platforms.

• Experience in SaaS product companies.

   

What You'll Do:

• Design, build, and optimize scalable data pipelines.
• Develop and maintain cloud-based data infrastructure on AWS.
• Process and transform large volumes of data using Spark/PySpark.
• Ensure data quality, reliability, and performance.
• Collaborate with product, engineering, and analytics teams.
• Improve existing data architecture and propose new solutions.
• Contribute to the scalability and evolution of the company's data platform.

What we offer:

• Remote job and flexible schedule.
• Full-time position.
• Fast-paced product environment with direct impact on product quality and processes.
• Performance-review.

Waiting for your CV!

Cargofy is building the AI-native operating system for global freight. Cargofy deploys autonomous AI agents that automate procurement, dispatching, negotiations, operations, tracking, and workflows for carriers, shippers, and 3PLs across the US, Europe, and Asia. Our platform processes 100,000+ loads per day and hundreds of thousands of real-time events — replacing manual logistics with fully autonomous AI.

We need an Integration Engineer (PHP/Laravel) to build and maintain the connectors that plug our AI agents into the systems logistics runs on — load boards, TMS platforms, telematics, finance, e-sign, and communication services. The catalog is large and growing constantly: there will always be a next connector.

Why This Role Matters

Our AI agents are only as capable as the systems they can reach. An agent that finds loads needs load boards like DAT. An agent that negotiates needs telephony and email. An agent that files documents needs e-sign. Every connector you ship gives every agent on the platform a new capability — and every customer gets it within days.

What You Will Do

• Build and maintain integrations with third-party systems: load boards, TMS and ERP platforms, telematics/ELD providers, LTL carriers, finance and e-sign services, messaging and telephony
• Design connectors that survive the real world: rate limits, flaky third-party uptime, breaking API changes, retries/backoff, idempotency
• Build two-way sync flows — loads in, statuses and documents back out — where the customer's system stays the system of record
• Wrap legacy APIs (SOAP/XML, government e-services) into clean internal interfaces our agents consume
• Own connector health: monitoring, alerting, and recovery for integrations processing events at scale

Tech Stack

• PHP 8.x — strong OOP, PSR standards, clean code
• Laravel — queues (Redis + Horizon), jobs, events, service container
• REST, OAuth2, webhooks; SOAP/XML for legacy APIs
• PostgreSQL, event-driven architecture
• PHPUnit, CI/CD pipelines, Docker

Who You Are

• 3+ years of production PHP/Laravel experience, with real third-party API integration work behind you
• You treat other people's APIs as a hostile environment — you design for failure, not the happy path
• You can read undocumented or badly documented APIs without waiting for support tickets
• Independent and proactive — a new connector is a project you scope and ship, not a task you receive
• Logistics domain experience (TMS, load boards, ELD) is a strong plus, not a requirement

Why Cargofy

• Your connector ships to production within days and immediately powers AI agents used by thousands of logistics companies
• Work at the frontier of applied AI — the integrations you build are what lets our agents make real phone calls, book real loads, and file real documents
• Competitive compensation + stock options for top performers
• Clear OKR system, strong engineering culture, and a team that ships daily
• Remote-first with offices in Kyiv, Warsaw, and Houston

Hi!

Our client is an international product company that helps hotel chains like Hilton and Marriott transform front-desk staff into revenue generators through upselling training and analytics. Their IN-Gauge SaaS platform empowers frontline teams across 2,000+ properties in over 100 countries.

Responsibilities:

• Design, build, and maintain scalable data pipelines and ETL/ELT processes on AWS
• Develop and optimize distributed data processing jobs using Spark/PySpark
• Ensure data quality, reliability, and performance in high-load environments
• Collaborate with product, analytics, and engineering teams to deliver data-driven solutions
• Monitor, troubleshoot, and improve existing data workflows
• Proactively identify bottlenecks and propose architectural improvements

Requirements:

• 5+ years of commercial experience in Data Engineering
• 3+ years of hands-on experience with AWS
• 2+ years of experience with Spark/PySpark 
• Experience working in high-load environments
• Autonomous and proactive mindset - ability to own tasks and drive them independently

We offer:

• Work on a product used by the world's leading hotel brands
• An international team and the opportunity to influence architectural decisions
• Flexible schedule and remote work
• Competitive compensation based on experience

Interested? Send us your CV - we'd love to talk!

Key Responsibilities

• Design, develop, and optimize deep learning models using PyTorch.
• Build and maintain scalable training and evaluation pipelines.
• Lead model selection, experimentation, and fine-tuning activities.
• Improve training performance, efficiency, and scalability across large datasets and compute environments.
• Work with multimodal data sources, including video, images, and audio.
• Provide technical guidance on AI architecture, training strategies, and best practices.
• Collaborate closely with product, engineering, and research teams to translate business objectives into AI solutions.
• Support deployment and operationalization of machine learning models in production environments.

Required Experience

• 5+ years of experience in Machine Learning, Data Science, or AI Engineering roles.
• Strong hands-on experience developing deep learning models with PyTorch.
• Proven experience building and optimizing training pipelines for machine learning systems.
• Deep understanding of model training, hyperparameter tuning, and performance optimization.
• Experience working with computer vision, audio processing, or multimodal AI applications.
• Strong software engineering skills and experience developing production-ready ML solutions.
• Experience with cloud-based or distributed training environments.

Preferred Qualifications

• Experience applying machine learning techniques within behavioral science, human behavior analysis, affective computing, or related domains.
• Experience with video understanding, speech/audio analysis, or multimodal foundation models.
• Familiarity with MLOps practices, model monitoring, and scalable deployment architectures.
• Experience working with large-scale datasets and distributed training frameworks.

About the company:

Kickbite is a fast growing all-in-one marketing analytic tool, which collects, analyzes, and visualizes e-commerce data all in one place. It provides actionable insights to all decision-makers to scale online sales and improve return of advertising spends. Website: https://www.kickbite.io/

Responsibilities:

- Creating and maintaining existing ETL processes

- Transform raw data and raw events into valuable data for business users

- Performing end-to-end data flow checks

- Integration with the new data sources

Requirements:

- 4-5 years of related experience

- Excellent knowledge of Python programming language

- Extensive experience with SQL DB's, Bigquery

- Strong knowledge of REST API

- Version Control Systems (GIT)

What we offer:

- Competitive level of compensation transferred directly to bank account

- Full-time remote work 40 hours per week (approximately from 10.00 to 18.00)

- 20 working days of vacation per year

- Paid sick leaves up to 2 weeks per year

- Free time for educational purposes

About the company:

Kickbite is a fast growing all-in-one marketing analytic tool, which collects, analyzes, and visualizes e-commerce data all in one place. It provides actionable insights to all decision-makers to scale online sales and improve return of advertising spends. Website: https://www.kickbite.io/

Responsibilities:

- Creating and maintaining existing ETL processes

- Transform raw data and raw events into valuable data for business users

- Performing end-to-end data flow checks

- Integration with the new data sources

Requirements:

- 4-5 years of related experience

- Excellent knowledge of Python programming language

- Extensive experience with SQL DB's, Bigquery

- Strong knowledge of REST API

- Version Control Systems (GIT)

What we offer:

- Competitive level of compensation transferred directly to bank account

- Full-time remote work 40 hours per week (approximately from 10.00 to 18.00)

- 20 working days of vacation per year

- Paid sick leaves up to 2 weeks per year

- Free time for educational purposes

Description
The ideal candidate brings solid Machine Learning and AI expertise, with hands-on experience building and operating data-driven and intelligent systems in production environments. Candidates must be comfortable defending architectural decisions and writing production-grade code in a high-performance environment.

Key Qualifications

Strong experience with Apache Spark, including optimization techniques for large-scale workloads
Strong experience with Spark Structured Streaming
Strong experience with Spark SQL and query performance optimization
Hands-on experience with Python for data processing, ML, and AI use cases
Practical experience in Machine Learning (ML), including model development and integration
Solid understanding of AI / GenAI concepts, with ability to apply them in real-world scenarios
Experience with Terraform and Databricks Asset Bundles
AI / ML Focus (Added Emphasis)

Proven practical ML experience, not only theoretical knowledge
Experience working with AI solutions before and/or during the GenAI era (classical ML is valuable)
Ability to integrate ML/AI components into scalable data platforms
Understanding of data pipelines supporting AI/ML workflows
Nice to Have

Familiarity with Databricks (good working knowledge; deep expertise is a plus but not required)
Experience with application development and Databricks Apps
Comfort working in Linux environments
Background in financial markets, such as market making, trading, or related domains
Knowledge of German or French is a plus
Working Style

Able to work independently, prioritize effectively, and proactively identify opportunities for improvement
Comfortable operating in a loosely defined scope, contributing not only to execution but also to defining priorities and driving work forward

We're looking for the right person to build that foundation from the ground up.
This is a hands-on leadership role with real ownership: you'll shape how data is collected, structured, and delivered — and grow a team around you as the function matures.

 

WHAT YOU'LL BE WORKING ON
 

• Design the target-state data architecture: Postgres CDC → Kafka → Snowflake → client-facing data products.
• Own tooling decisions across ingestion, orchestration, transformation, and quality layers.
• Implement CDC-based ingestion from PostgreSQL services (RDS, Aurora, EC2, K8s operator) using Debezium or equivalent.
• Build streaming and near-real-time pipelines with defined SLAs.
• Build a data quality control layer: checksums, reconciliation, schema validation, anomaly detection, and alerting.
• Define quality checkpoints across the full pipeline — from source capture through Snowflake to client delivery.
• Define and enforce data contracts with service-owning teams for core entities: transaction, merchant, settlement, and processing status.
• Build the external data delivery layer: financial settlement, transaction status, processor reconciliation, and client analytics.
• Design tenant separation and implement replay/reload mechanisms for failure recovery.
• Start hands-on, then gradually hire and grow a small data engineering team as the function matures.
  Build a pragmatic roadmap with concrete deliverables at 3, 6, and 12 months.
   

WHAT YOU NEED TO SUCCEED IN THIS ROLE
 

• 5+ years in data engineering with end-to-end ownership of production pipelines.
• Hands-on with Snowflake, PostgreSQL CDC (Debezium preferred), and Kafka.
• Solid AWS experience — S3, RDS, Aurora, and cloud data infrastructure.
• Data quality engineering mindset: monitoring, reconciliation, lineage.
• Comfortable defining data contracts and driving requirements with backend engineering teams.
• Technical leadership experience: project ownership, cross-team alignment, delivery under constraints.
• Kubernetes, Airflow/Prefect/Dagster, and dbt are strong pluses.
• Payments domain knowledge — settlement, transaction lifecycle, processor integrations — is a strong plus.
• Familiarity with gRPC, RabbitMQ, and reading Go/Python service code is expected.

• Project Description:

  Owns the technical direction, quality, and delivery enablement of the data platform within the team. Ensures scalable architecture, reliable releases, and strong engineering practices while enabling the team to deliver efficiently within defined engineering and release standards.

• Responsibilities:

  Architecture & Technical Ownership
  • Owns end-to-end technical design across Snowflake, dbt, ADF, and Azure components
  • Acts as the final technical decision authority within the team
  • Ensures alignment with enterprise architecture and data governance standards
  • Maintains architecture documentation and diagrams
  ________________________________________
  Engineering Excellence
  • Defines and enforces coding standards and best practices
  • Reviews critical PRs and ensures maintainability and scalability
  • Drives performance optimization and cost efficiency
  • Continuously improves development efficiency by reducing technical complexity and removing bottlenecks
  ________________________________________
  CI/CD & Release Ownership
  • Owns and improves CI/CD pipelines and deployment processes
  • Defines and enforces the release process, ensuring it is standardized and consistently followed
  • Establishes release criteria based on Definition of Done, testing, and required approvals
  • Ensures all changes meet release criteria before deployment to production
  • Oversees and coordinates production releases, including validation of readiness and risk assessment
  • Has authority to block releases that do not meet defined quality and governance standards
  • Ensures pipelines enforce quality gates (tests, validations, approvals where required)
  • Continuously improves release safety and reduces production incidents
  ________________________________________
  Quality & Definition of Done
  • Ensures adherence to Definition of Done (including testing and documentation)
  • Works with QA and team to ensure test coverage aligns with acceptance criteria
  ________________________________________
  Team Enablement & Mentoring
  • Mentors engineers and supports technical growth
  • Leads knowledge sharing and supports complex problem-solving
  ________________________________________
  Planning & Delivery Support
  • Contributes to sprint planning with technical estimates, risks, and dependencies
  • Owns identification and prioritization of technical debt in collaboration with the Product Owner
  ________________________________________
  Production Ownership
  • Leads incident analysis and root cause resolution
  • Ensures monitoring, alerting, and data quality validation mechanisms are in place across pipelines and in production
  • Maintains runbooks for operational readiness
  ________________________________________
  Ways of Working
  • Collaborates closely with Product Owner and Scrum Master to align technical delivery with business priorities; supports team continuity and helps facilitate meetings when the Scrum Master is absent
  • Proactively works with upstream data source teams and other squads to resolve cross-team dependencies, data issues, and production bugs
  • Drives technical alignment across teams/squads where shared data models, pipelines, or integrations are involved
  • Acts as the primary technical point of contact for external teams and stakeholders

• Mandatory Skills Description:

  7+ experience in Data Engineering and development of DWH solutions
  Hands-on experience with Snowflake, dbt, Azure Data Factory
  Experience with Azure Cloud Solutions, Azure DevOps
  Practical experience and understanding of CI/CD processes
  Experience of technical leadership in Agile SDLC

• Nice-to-Have Skills Description:

  Experience with AWS and/or GCP cloud solutions
  Certifications related to DWH

• Languages:
  • English: C1 Advanced

We are seeking a motivated Junior Big Data Engineer to join our team. In this role, you will contribute to the development and maintenance of data pipelines, data models, and data processing solutions within modern cloud and big data environments. You will work closely with senior engineers to build scalable data solutions and support data-driven business initiatives.

The ideal candidate has hands-on experience with Python, PySpark, and SQL, a solid understanding of data engineering fundamentals, and an interest in working with large-scale data platforms and AI-powered solutions.

Key Responsibilities:

• Support the design, development, and maintenance of data pipelines and ETL/ELT processes.
• Develop and optimize data transformation workflows using Python and PySpark.
• Assist in integrating data from multiple sources while ensuring data quality, consistency, and reliability.
• Collaborate with data engineers, data scientists, and AI/ML engineers to prepare and manage datasets for analytics and machine learning applications.
• Participate in data modeling, schema design, and data warehousing activities.
• Monitor data pipelines, investigate issues, and contribute to performance improvements.
• Follow data governance, security, and privacy best practices.
• Document technical solutions, processes, and data flows.
• Stay current with emerging technologies and industry trends, incorporating innovative solutions into data engineering practices, and effectively document and communicate technical solutions and processes.

Tools and skills you will use in this role:

• Palantir Foundry
• Python
• PySpark
• SQL
• TypeScript

Requirements:

• 1+ year of experience in data engineering
• Strong proficiency in Python and SQL
• Hands-on experience with PySpark
• Familiarity with big data technologies (e.g., Apache Hadoop, Spark, Kafka, BigQuery, etc.)
• Basic experience with cloud services (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow)
• Understanding of ETL/ELT pipelines and data integration techniques
• Experience with database systems (e.g., PostgreSQL, MySQL, NoSQL, etc.)
• Effective problem-solving and analytical skills, coupled with excellent communication and collaboration abilities
• Strong communication and teamwork abilities
• Strong mathematical, statistical, and algorithmic skills
• English - Upper-Intermediate or higher

Nice to have:

• Experience with AI/ML
• Previous experience working with JavaScript and TypeScript

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