Ukraine
We are looking for a Data Engineer to join one of the largest and strongest Data Units in Ukraine.
With more than 220+ experts and over 30 ongoing projects across the EU and US, our Data Unit contributes to industries ranging from agriculture to satellite communications and fintech. We work with cutting-edge technologies, handle massive data volumes, and provide our engineers with opportunities to grow from mentoring roles to becoming solution architects.
Join our ambitious Data team, where business expertise, scientific approach, and advanced engineering meet to unlock the full potential of data in decision-making.
Our client is a US-based global leader in in-flight Internet and entertainment services, serving 23 commercial airline partners and nearly 3,600 aircraft worldwide. They also provide connectivity solutions for maritime and government sectors and are one of the world’s largest satellite capacity providers.
For over six years, N-iX has been supporting the client across Business Intelligence, Data Analysis, Data Science, and Big Data domains. We are now expanding the team with a Big Data Engineer who will help enhance complex data management and analytics solutions.
As a Data Engineer, you will work closely with the client’s Data Science team, supporting the end-to-end lifecycle of data-driven solutions — from designing and building data pipelines to deploying ML models into production. You’ll play a key role in ensuring high-quality data for model training and inference, as well as contributing to scalable architecture design.
Design, develop, and maintain data pipelines and large-scale processing solutions.
Build and support environments (tables, clusters) for data operations.
Work with AWS SageMaker to deploy ML models into production.
Collaborate with Data Scientists to prepare and validate datasets.
Implement and support data validation frameworks (e.g., Great Expectations).
Migrate PySpark code into optimized DBT SQL queries.
Contribute to solution architecture and ensure scalability of workflows.
Strong programming skills in Python (Pandas, PySpark).
Proficiency in SQL for data modeling and transformations (DBT knowledge is a plus).
Experience with the AWS ecosystem (Lambda, EMR, S3, DynamoDB, etc.).
Solid understanding of data pipeline orchestration.
Experience with Airflow for workflow automation.
Knowledge of Docker for containerized deployments.
Familiarity with data validation frameworks (Great Expectations).
Hands-on experience with Snowflake or other cloud data warehouses.
Exposure to ML data preparation.
We offer*:
*not applicable for freelancers
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