Senior Data Engineer (Databricks)
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AddeptoData engineering
Workplace type: remote; Locations: Warszawa, Krucza 50, Kraków, Aleksandra Lubomirskiego 20, Wrocław, Świdnicka 40, Katowice, -, Gdańsk, -, Warszawa, Country code: PLFull-TimeSenior
Salary21000 - 28560 PLN per month net b2b
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Job Details
- Experience
- At least 5 years of commercial experience implementing, developing, or maintaining Big Data systems.
- Required Skills
- PythonSQLApache AirflowMicrosoft Power BIApache KafkaAzureSparkdbtDatabricks
Requirements
- Have at least 5 years of commercial experience implementing, developing, or maintaining Big Data systems.
- Demonstrate strong Python programming skills, including clean code and object-oriented design.
- Have strong SQL skills, including performance tuning, query optimization, and data warehousing experience.
- Have experience designing and implementing data governance and data management processes.
- Bring expertise in Databricks, Spark, Kafka, EventHub, Airflow, Dagster, and modern data orchestration and transformation tools.
- Have experience implementing and deploying solutions in cloud environments; Azure is preferred.
- Know how to build and deploy Power BI reports and dashboards.
- Understand dimensional data and data modeling techniques.
- Have consulting experience and the ability to guide clients on architecture, technology selection, and best practices.
- Be able to work independently and own project deliverables.
- Hold a Master’s or Ph.D. in Computer Science, Big Data, Mathematics, Physics, or a related field.
Responsibilities
- Design and optimize scalable data processing pipelines for streaming and batch workloads using Databricks, Apache Airflow, and Dagster.
- Architect and implement end-to-end data platforms for high availability, performance, and reliability.
- Lead CI/CD and MLOps processes for deployment, monitoring, and model lifecycle management.
- Develop and maintain applications that aggregate, process, and analyze data from diverse sources.
- Collaborate with Data Science teams on machine learning projects, including feature engineering and predictive model deployment.
- Design and manage data transformations using Databricks, DBT, and Apache Airflow.
- Translate business requirements into technical solutions while maintaining performance and data quality.
- Apply data security, compliance, and governance practices across data pipelines.
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