Experience: 5 - 20 Years Location: USA - Glendale Must-Have • 5+ years of data engineering experience, specifically developing large-scale data pipelines • Experience with Spark, Airflow, Databricks or Snowflake, SQL, Python Location: Glendale, CA – Onsite 4 days a week The Company Headquartered in Los Angeles, this leader in the Entertainment & Media space is focused on delivering world-class stories and experiences to its global audience. To offer the best entertainment experiences, their technology teams focus on continued innovation and utilization of cutting-edge technology. Platform / Stack You will work with technologies that include Python, AWS, Spark, Snowflake, Databricks, and Airflow. What You'll Do As a Sr Data Engineer • Contribute to maintaining, updating, and expanding existing Core Data platform data pipelines • Build and maintain APIs to expose data to downstream applications • Develop real-time streaming data pipelines • Utilize a tech stack including Airflow, Spark, Databricks, Delta Lake, and Snowflake • 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 meet SLAs and project reliability and accuracy expectations Qualifications You could be a great fit if you have: • 5+ years of data engineering experience developing large data pipelines • Proficiency in at least one major programming language (e.g., Python, Java, Scala) • 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 • Advanced understanding of OLTP vs OLAP environments • Strong background in distributed data processing, software engineering of data services, or data modeling Skills: graphql,spark,aws,data modeling,delta lake,data,pipelines,database,sql,snowflake,data engineering,api development,technology,oltp,java,airflow,scala,apache spark,core data,python,databricks,olap,large-scale data pipelines