AWS Lead Data Engineer

2 weeks ago


Remote, Czech Republic Link Group Full time
  • 7+ years of experience in data engineering, including 2+ years in a leadership or architecture role.
  • Expertise in Airflow, Snowflake, DBT, and advanced knowledge of Python, Spark, SQL, and AWS.
  • Proven experience in designing and deploying large-scale data warehouses and building complex data models.
  • Hands-on experience with third-party APIs and external data sources.
  • Strong ability to optimize system performance, streamline ETL workflows, and enhance data storage solutions.
  • Excellent communication skills with the ability to bridge technical teams and business stakeholders.

Preferred Skills

  • Understanding of adtech ecosystems (DSPs, ad servers, etc.).
  • Familiarity with tools like Apache Druid, AWS Glue, and PySpark (current stack, slated for replacement).
  • Experience defining data governance policies and implementing best practices for data management.
  • Knowledge of CI/CD tools and modern DevOps practices.
,[Lead and mentor a team of data engineers while actively contributing to pipeline development, architecture design, and system optimization., Design and implement scalable, high-performance data architectures., Build and manage ETL pipelines using Airflow, Snowflake, and DBT., Establish and enforce best practices for data partitioning, retention, security, and governance., Collaborate with stakeholders to align data solutions with business objectives and promote a data-driven culture., Continuously drive innovation in data engineering processes and architecture strategies., Translate business requirements into technical specifications and maintain comprehensive documentation.] Requirements: AWS, Airflow, Snowflake, dbt, Python, Spark, SQL, Agile, Data warehouses, Data models, ETL, DSPs, AD, Apache Druid, AWS Glue, PySpark, DevOps, CI/CD Tools: Agile, Scrum.
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