Senior Data Engineer

Job Title: Data Engineer

Job Type: Full-time

Job Location: Glendale, CA or Burbank, CA

Key Responsibilities:

• Contribute to maintaining, updating, and expanding existing Core Data platform data pipelines
• Build tools and services to support data discovery, lineage, governance, and privacy
• Collaborate with other software/data engineers and cross-functional teams
• Tech stack includes Airflow, Spark, Databricks, Delta Lake, Snowflake, Kubernetes and AWS
• Collaborate with product managers, architects, and other engineers to drive the success of the Core Data platform
• Contribute to developing and documenting both internal and external standards and best practices for pipeline configurations, naming conventions, and more
• Ensure high operational efficiency and quality of the Core Data platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams)
• Be an active participant and advocate of agile/scrum ceremonies to collaborate and improve processes for our team
• Engage with and understand our customers, forming relationships that allow us to understand and prioritize both innovative new offerings and incremental platform improvements
• Maintain detailed documentation of your work and changes to support data quality and data governance requirements

Technology and Expertise:

• 5+ years of data engineering experience developing large data pipelines
• Proficiency in at least one major programming language (e.g. Python,Java, Scala)
• Strong SQL skills and ability to create queries to analyze complex datasets
• Hands-on production environment experience with distributed processing systems such as Spark
• Hands-on production experience with data pipeline orchestration systems such as Airflow for creating and maintaining data pipelines
• Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Databricks, Big Query).
• Experience in developing APIs with GraphQL
• Deep Understanding of AWS or other cloud providers as well as infrastructure as code
• Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices
• Strong algorithmic problem-solving expertise
• Excellent written and verbal communication
• Advance understanding of OLTP vs OLAP environments
• Willingness and ability to learn and pick up new skill sets
• Self-starting problem solver with an eye for detail and excellent analytical and communication skills
• Strong background in at least one of the following: distributed data processing or software engineering of data services, or data modeling
• Familiar with Scrum and Agile methodologies