Senior Data Engineer

New

DataArtData engineering

Workplace type: remote; Country code: PLFull-TimeSenior

Salary19,000 - 22,500 PLN per month

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Job Details

Languages: English B2
Experience: 5+ years of Data Engineering or related experience; 2+ years of hands-on experience with Snowflake and dbt
Required Skills: AWSPythonSQLApache AirflowGitSnowflakeCI/CDTerraformdbt

Have 5+ years of Data Engineering or related experience.
Have 2+ years of hands-on experience with Snowflake and dbt.
Have production experience implementing and supporting Fivetran pipelines.
Have experience designing reusable ingestion and transformation patterns.
Demonstrate strong SQL skills, including complex joins, CTEs, window functions, reconciliation, and query optimization.
Have experience with Git and CI/CD, including branching, pull requests, code reviews, and automated deployment workflows.
Have working knowledge of Python for data processing, automation, API integrations, file processing, data validation, and operational scripting.
Have experience operating within enterprise DEV, QA, and PROD SDLC and change management processes.
Have production troubleshooting and root cause analysis skills.
Be comfortable using Claude, Cursor, or VS Code with AI-assisted development capabilities.
Apache Airflow or AWS MWAA orchestration experience is a plus.
Experience with AWS services, SaaS integrations, REST API, SFTP, Snowpark, Databricks, Terraform, or data quality and observability frameworks is a plus.

Design end-to-end data pipelines using Fivetran, dbt, and Snowflake.
Build and support ingestion and transformation pipelines for enterprise data products.
Configure and manage Fivetran connectors across SaaS applications, databases, APIs, and file-based sources.
Develop and maintain dbt models across staging, intermediate, mart, and publish layers.
Implement dbt tests, source freshness checks, incremental processing, documentation, and reusable macros.
Develop optimized Snowflake SQL and scalable analytical data models.
Support Snowflake objects, security and RBAC, stages, data sharing, and data loading patterns.
Implement data quality, reconciliation, monitoring, and operational alerting.
Troubleshoot production pipelines and perform root cause analysis across ingestion and transformation layers.
Participate in Git-based development, CI/CD, code reviews, and DEV, QA, and PROD deployments.

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