Data Engineer

Technologies we use

About the project

Your responsibilities

• Design, develop, and deploy Python-based ETL pipelines using Airflow and Prefect
• Build and optimize data warehouse structures for analytics, OLAP, and dimensional modeling
• Model AI-compatible DB schemas and ontologies for future-facing analytics
• Migrate and transform structured, semi-structured, and unstructured data using DBT and Pandas
• Work with streaming/event-driven architectures for real-time data processing
• Optimize pipeline performance and scalability for large data volumes
• Ensure data quality, validation, cleansing, and graceful error handling
• Perform code reviews to ensure standards, scalability, and best practices
• Collaborate with DevOps on CI/CD and automated release pipelines
• Implement data governance, security, and observability across ETL processes

Our requirements

• 5+ years of experience designing and building enterprise-scale ETL pipelines
• Strong Python skills, including use of Pandas for data processing
• Proficient in SQL — writing complex queries and procedures across RDBMSes
• Experience with Airflow, Prefect, or similar workflow orchestration tools
• Solid understanding of data warehousing (OLTP, OLAP, Facts & Dimensions)
• Familiarity with cloud-based data platforms such as RDS, Redshift, or Snowflake
• Knowledge of cloud data architectures, messaging systems, and scalable design
• Hands-on experience with code versioning, deployment automation, and CI/CD

Optional

• Experience with Docker, Kubernetes, AWS Lambdas, Step Functions
• Exposure to Databricks, PySpark, and advanced distributed data processing
• Cloud certifications are a plus

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This is how we work

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What we offer

• B2B contract with monthly compensation up to $7,800
• Strong career growth opportunities in a global fintech environment
• High-impact projects in a fast-growing sector
• Friendly, open, and ambitious team culture
• Hybrid model – minimum 3 days/week in the Warsaw office

Benefits