Senior Data Engineer
⚲ Warsaw
Do uzgodnienia
Wymagania
- Data modeling
- Microsoft SQL Server
- PostgreSQL
- SQL
- DataStage (ETL)
- ETL
- Cloud
- Microsoft Azure
- Microsoft Platform
- Spark
Opis stanowiska
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
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
🔍 Dekoder Ogłoszenia
🔴
enhance the organization's analytical capabilities
Twoja praca będzie polegać na budowaniu podstawowych narzędzi do analizy, a nie na samej analizie.
🔴
meet business needs
Często oznacza to konieczność szybkiego dostosowywania się do zmieniających się priorytetów biznesowych, nawet jeśli nie są one technicznie optymalne.
🔴
Work with structured and semi-structured data from multiple sources
Może oznaczać konieczność radzenia sobie z chaotycznymi, niepełnymi lub źle zdefiniowanymi danymi.
🟡
Ability to work independently and collaboratively within a data team
Oczekuje się, że będziesz samodzielny, ale jednocześnie łatwo dopasujesz się do dynamiki zespołu i jego potrzeb.
🟡
Exposure to dbt, Delta Lake, or data warehousing concepts
Jest to mile widziane, ale nie jest wymagane, co może sugerować, że nie są to kluczowe technologie dla tej roli.