Lead Data Engineer AWS

• 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.

Required Skills & Experience

• 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.