Senior Data Engineer
New
D
DataArtData engineering
Workplace type: remote; Locations: Wrocław, plac Grunwaldzki 23, Warszawa, Prosta 20, Lublin, Tomasza Zana 39a, Kraków, Jana Dekerta 24, Łódź, Gdańska 130, Wrocław, Country code: PLFull-TimeSenior
Salary20,000 - 26,000 PLN per month
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Job Details
- Languages
- En B2
- Experience
- 5+ years of experience or 5+ completed projects
- Required Skills
- AWSPythonSQLSnowflakeAzureSparkdbtDatabricks
Requirements
- Have 5+ years of experience or 5+ completed projects.
- Bring advanced SQL skills, including query optimization and proficiency across popular database variations.
- Use Python for data engineering and automation.
- Have experience with Snowflake and/or Databricks.
- Have experience with AWS and/or Azure cloud services.
- Use DBT for data transformation and modeling.
- Design, develop, and maintain ETL/ELT pipelines.
- Have Apache Spark experience; PySpark is preferred.
- Use Apache Airflow, Dagster, or another widely adopted workflow orchestrator.
- Understand relational database design and performance tuning.
- Know data warehousing concepts and dimensional modeling.
- Understand data modeling, data quality, metadata management, warehouse/lake patterns, and distributed systems.
- Use Git and CI/CD practices, and understand data governance, lineage, observability, and cloud data platform security and access control.
Responsibilities
- Develop, operate, optimize, test, and maintain the data warehouse, including ETL/ELT processes, cubes, database and performance administration, and dimensional tables.
- Drive the full lifecycle of back-end development for the data warehouse.
- Identify and implement process improvements by redesigning infrastructure for scalability, optimizing data delivery, and automating manual processes.
- Define data retention policies.
- Build analytical tools that use the data pipeline to deliver insight into business metrics such as operational efficiency and customer acquisition.
- Select and integrate tools for monitoring, managing, and alerting on database performance.
- Develop automated processes for uninterrupted database updates and vulnerability correction.
- Assemble complex datasets that meet functional and non-functional business requirements.
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