Senior Data Migration Engineer
NewInactive
S
SiiData Engineering
Locations: Łódź, -, Lublin, -, Bydgoszcz, -, Kraków, -, Gdańsk, -, Katowice, -, Poznań, -, Rzeszów, -, Szczecin, -, Wrocław, -, Białystok, -, Piła, -, Toruń, -, Warszawa, -, Łódź, Country code: PLFull-TimeSenior
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Salary not disclosed
Job Details
- Languages
- Advanced level of English, Advanced level of Polish
- Experience
- At least 5 years
- Required Skills
- PythonCloud ComputingETLGitMicrosoft SQL ServerSnowflakePandas
Requirements
- At least 5 years of hands-on experience developing and maintaining enterprise data warehouse solutions
- Strong expertise in Microsoft SQL Server (T-SQL) and Snowflake, including performance optimization, stored procedures, views, functions, and query tuning
- Proven experience migrating SQL Server workloads to Snowflake or another cloud data warehouse
- Hands-on commercial experience with Snowflake, including knowledge of its architecture and performance optimization techniques
- Strong Python skills for data engineering, with practical experience using pandas and pytest for automated testing and data validation
- Experience using AI coding assistants in professional software development, with the ability to review and productionize AI-generated code
- Advanced level of English
- Experience with Matillion ETL and building production ELT pipelines
- Knowledge of traditional data warehousing concepts and exposure to cloud/data platforms such as AWS or Azure
- Advanced level of Polish
Responsibilities
- Migrating database objects such as stored procedures, views, functions, and ETL logic from Microsoft SQL Server to Snowflake while ensuring functional equivalence
- Designing, developing, and optimizing Matillion ELT pipelines for loading and transforming data into Snowflake
- Building automated data validation and reconciliation frameworks in Python to compare source and target datasets during migration
- Analyzing and resolving data discrepancies related to data type conversions, SQL dialect differences, and transformation logic
- Leveraging AI coding assistants to accelerate code conversion and refactoring, while reviewing and productionizing AI-generated code
- Optimizing Snowflake performance by tuning queries, virtual warehouses, clustering strategies, and transformation workloads
- Creating automated testing suites to validate migration results and prevent regressions throughout the delivery lifecycle
- Implementing CI/CD processes using Git and deployment pipelines to manage database, Snowflake, and Matillion releases across environments