Senior Data Engineer
New
L
Link GroupData engineering
Workplace type: remote; Locations: Kraków, Centrum, Kraków, Country code: PLContractSenior
Salary130 - 165 PLN per hour
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Job Details
- Experience
- 10+ years of progressive software/data engineering experience; 5+ years of deep, hands-on expertise within the Databricks ecosystem.
- Required Skills
- PostgreSQLPythonSQLAzureSparkDatabricksGitLab
Requirements
- Hold an advanced degree (Master’s or equivalent) in Computer Science, Engineering, or a related technical discipline.
- Have 10+ years of progressive software/data engineering experience.
- Have 5+ years of deep, hands-on expertise in the Databricks ecosystem.
- Have hands-on experience with Python, Apache Spark, Delta Lake, and Delta Live Tables (DLT).
- Have a proven track record architecting solutions across data warehouses, data lakes, and lakehouse architectures.
- Have experience engineering high-throughput, fault-tolerant pipelines for batch and real-time streaming workflows.
- Have an architectural background focused on low-latency processing, high data availability, and horizontal scalability.
- Have database engineering skills across SQL, PostgreSQL, Azure SQL, and PL/SQL.
- Have familiarity with cloud platforms, preferably Azure, and Linux/Unix environments and shell scripting.
- Have production experience establishing CI/CD workflows and automated test suites using GitLab and industry-standard tools.
- Be able to validate proofs of concept and develop them into production-grade systems following clean code principles.
Responsibilities
- Architect enterprise big data solutions across data warehouses, data lakes, and lakehouse architectures.
- Engineer high-throughput, fault-tolerant pipelines for massive datasets.
- Build batch and real-time streaming workflows.
- Design systems for low-latency processing, high data availability, and horizontal scalability.
- Establish CI/CD workflows and automated test suites using GitLab and industry-standard tools.
- Prototype proofs of concept and harden validated solutions into production-grade systems.
- Apply AI-assisted engineering tools throughout the software development lifecycle.
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