Data Engineer (Python / Databricks / Azure / Czech Speaker)

We are looking for a hands-on Data Engineer to join a modern Data Warehouse team responsible for building scalable cloud-native data solutions. You will design, develop, and maintain reliable ETL/ELT pipelines, optimize data models, and ensure high-quality data products for business users and downstream applications. The ideal candidate has strong experience with Python, SQL, Databricks, Azure, and modern Data Warehouse architecture, and enjoys working in an agile environment with close collaboration across engineering and business teams.

Responsibilities

Data Engineering & Pipeline Development Design, develop, and maintain scalable ETL/ELT pipelines using Python and SQL within Databricks. Build and optimize Delta Lake-based data solutions. Develop robust cloud-native data pipelines processing structured and semi-structured datasets. Implement automated data validation, monitoring, and testing.

Troubleshoot pipeline failures and optimize performance. Ensure data quality, reliability, and freshness. Data Warehouse Development Design and maintain Data Warehouse layers (Raw, Cleansed, Curated, Data Mart). Develop efficient data models following best practices. Optimize storage formats including Delta Lake and Parquet.

Collaborate on DWH architecture and governance. Analytics & Business Support Build analytical datasets for reporting and self-service BI. Support business stakeholders with complex data requests. Document datasets, transformations, metadata, and data lineage. Collaborate with Analytics, Data Science, and Product teams.

Requirements

Must Have Strong Python programming skills Advanced SQL (joins, CTEs, window functions, query optimization) Hands-on experience with Databricks Notebooks Jobs Delta Lake Unity Catalog Experience building production ETL/ELT pipelines Experience with Microsoft Azure Azure Data Lake Storage (ADLS) Azure Data Factory (ADF) is an advantage Good understanding of Data Warehouse concepts Experience with cloud-native data platforms Knowledge of data quality and testing practices Experience working in Agile teams Nice to Have Apache Spark / Py.

Spark Azure Data Factory Kafka or other streaming technologies Databricks MLflow Data governance Data lineage JSON Parquet CI/CD for data platforms Soft Skills Strong analytical mindset Attention to detail Ownership and accountability Excellent communication skills Ability to explain technical concepts to non-technical stakeholders Self-driven and proactive Team player Experience 2–5+ years in Data Engineering or Analytics Engineering Proven experience delivering production data pipelines Experience working within Azure cloud environments Experience supporting enterprise Data Warehouse solutions Technology Stack Cloud Microsoft Azure Data Platform Databricks Delta Lake Unity Catalog Workflows Languages Python SQL Storage Delta Parquet JSON Data Engineering ETL / ELT Data Warehouse Data Modelling Data Quality Nice to Have Spark / Py.

Spark Kafka Azure Data Factory MLflow Benefits Location: Czech Republic Industry: e-commerce Freelance/B2B Engagement: full-time allocation, long-term Project Start: summer 2026