Senior Data Engineer
Summary
Builds and optimizes SQL-based data pipelines on Databricks to model and transform data for analytics, using star and snowflake schemas.
The primary objective of the Data Engineer role is to enhance the organization's analytical capabilities by developing and managing SQL-based data solutions on the Databricks platform. This position aims to ensure robust data modeling and transformation processes that meet business needs.
Main Responsibilities:
Develop and maintain SQL-based data pipelines and transformation logic on Databricks.
Design, implement, and optimize star and snowflake schemas for analytical workloads.
Write and tune advanced SQL queries for reporting, aggregation, and data validation.
Collaborate with data engineers and analysts to ensure data models meet business needs.
Work with structured and semi-structured data from multiple sources.
Contribute to improving data quality, performance, and maintainability.
Key Requirements:
Solid experience with SQL (including analytical functions, joins, subqueries, CTEs, window functions, etc.).
Practical experience with Databricks, Spark, SQL, or similar distributed SQL engines.
Strong understanding of data modeling principles, particularly star and snowflake schemas.
Experience with relational databases (e.g., PostgreSQL, SQL Server, or similar).
Familiarity with ETL/ELT concepts and best practices.
Ability to work independently and collaboratively within a data team.
Nice to Have:
Exposure to dbt, Delta Lake, or data warehousing concepts.
Experience with cloud platforms (Azure, GCP, or AWS).
Other Details:
Location: Poland, Remote
Team Structure: Collaborates with data engineers and analysts