Senior Data Engineer

What you'll do

• Build and maintain product-driven initiatives to expand Identity and Device data product offerings.
• Develop scalable, fault-tolerant data processing pipelines for real-time and batch data delivery.
• Enhance the underlying codebase to ensure it is extensible, reusable, and maintainable.
• Increase unit test coverage on the existing codebase to improve software quality.
• Redesign data models to modernize products, improve performance, and decrease costs.
• Participate in code reviews and provide technical problem-solving for the engineering team.
• Participate in on-call support to ensure production system reliability.
• Articulate technical decisions and outcomes to product managers, designers, and other stakeholders.

What we're looking for

• Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field of study.
• 5+ years of related big data engineering experience modeling and developing large data pipelines.
• Hands-on experience with distributed systems such as Databricks compute using Spark, Presto, and Hive to process petabyte-level datasets.
• Strong Python, Scala/Spark, and SQL skills for processing big datasets.
• Experience with at least one major MPP or cloud database technology such as Snowflake, Redshift, Big Query, or Databricks.
• Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices.
• Operational experience as a point-of-contact or SME in multi-system/services production environments.
• Solid experience with data integration and orchestration toolsets (e.g. Airflow), CI/CD, and AWS S3.
• Demonstrated ability with cloud infrastructure technologies, including Terraform (preferred).
• Understanding of householding algorithms and third-party data enrichment tools (preferred).