Senior Data Engineer (Snowflake & Databricks)
New
I
ItransitionData engineering
Workplace type: remote; Locations: Warszawa, Al. Jerozolimskie 123A, Wrocław, Powstańców Śląskich 15, Warszawa, Country code: PLFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- En B2
- Experience
- 5+ years of hands-on data engineering experience
- Required Skills
- PythonSQLSnowflakeAzureData engineeringCI/CDData modelingdbtDatabricksPySpark
Requirements
- Bring 5+ years of hands-on data engineering experience, including delivery and support of production data solutions.
- Have practical experience with both Snowflake and Databricks.
- Use SQL and Python, including hands-on PySpark experience.
- Have experience using dbt to develop, test, and maintain data transformations.
- Have experience designing and deploying cloud data solutions, preferably on Azure.
- Have strong data modeling skills, including dimensional modeling and understanding of Data Vault 2.0 concepts.
- Have experience with Git, code reviews, automated testing, and CI/CD.
- Be able to investigate data quality issues and troubleshoot pipeline failures and performance problems.
- Have experience working directly with clients or multiple stakeholder groups.
- Be able to work independently, clarify ambiguous requirements, and take ownership of delivery.
- Apply critical thinking and problem-solving to evaluate alternatives and make evidence-based decisions.
- Work effectively in agile and startup environments, adapting to changing priorities and evolving requirements.
Responsibilities
- Work with client stakeholders to understand business needs, assess existing systems, and define technical requirements.
- Contribute to solution design by explaining technical options, trade-offs, and implementation effort.
- Design, build, and maintain production ETL/ELT pipelines integrating databases, APIs, and file-based sources.
- Develop data models and transformation workflows for analytics and business processes.
- Implement incremental loading, data validation, error handling, monitoring, and recovery mechanisms.
- Improve pipeline performance and manage compute and storage costs.
- Apply data security and governance practices, including access control and protection of sensitive data.
- Use version control, code reviews, automated testing, and CI/CD to deliver maintainable solutions.
- Create technical documentation and support knowledge transfer to client teams.
- Support project estimation and planning, raise delivery risks, and mentor other engineers.
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