
Data Engineering Lead for High-Performance Data Architectures
2 days ago
About the Role
We are seeking an experienced Data Engineering Lead to join our team at Link Group. This is a unique opportunity to lead and mentor a team of data engineers while actively contributing to pipeline development, architecture design, and system optimization.
Key Responsibilities
- Design and implement scalable, high-performance data architectures that meet business needs.
- Build and manage ETL pipelines using Airflow, Snowflake, and DBT to ensure seamless data flow.
- Establish and enforce best practices for data partitioning, retention, security, and governance to maintain data integrity.
- 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 to stay ahead of the curve.
Requirements
- 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.
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