Data Engineer - 1668
About The Position
The Data Engineer will develop and maintain data pipelines for marketing acquisition reporting, using Databricks, PySpark, and SQL. The role includes migrating existing Snowflake SQL scripts and transformations into Databricks Unity Catalog, building ingestion pipelines for external marketing vendor data, and supporting reliable, accurate reporting datasets. The position focuses on parsing, normalizing, transforming, and validating data; implementing data quality checks and monitoring alerts; troubleshooting pipeline failures; and improving processing performance, SLA monitoring, logging, and pipeline reliability. The engineer will collaborate with analytics teams and participate in code reviews, documentation, and engineering best practices. The role is hybrid, onsite Monday through Thursday and remote Friday, in Santa Monica, Burbank, or Glendale, California. It is a six-month contract-to-hire position with a rate of up to $92.50 per hour on W-2.
Requirements
- At least four years of professional Data Engineering experience or equivalent.
- Strong SQL skills, including complex joins, window functions, and analytical queries.
- Hands-on production experience with PySpark and/or Spark SQL.
- Experience building production pipelines in Databricks.
- Experience with Databricks, including Delta Lake and Unity Catalog.
- Strong understanding of ETL/ELT pipelines, data modeling, and distributed processing.
- Strong understanding of Lakehouse architecture and data governance.
- Experience with AWS services such as S3, IAM, EC2, Glue, or Lambda.
- Experience with Apache Airflow or similar orchestration tools.
- Experience processing JSON, Parquet, CSV, and other semi-structured data.
- Experience with Git/GitHub, CI/CD, and modern DevOps practices.
Nice To Haves
- Experience migrating SQL transformations from Snowflake to Databricks.
- Experience working with marketing acquisition or advertising data.
- Experience implementing data quality monitoring and pipeline reliability improvements.
Responsibilities
- Develop and maintain ETL/ELT pipelines using Databricks, PySpark, and SQL for marketing acquisition reporting.
- Migrate existing Snowflake SQL scripts and transformations into Databricks Unity Catalog.
- Build ingestion pipelines for external marketing vendor data.
- Perform data parsing, normalization, transformation, and validation.
- Implement data quality checks, monitoring alerts, and issue resolution workflows.
- Troubleshoot pipeline failures and improve processing performance.
- Support SLA monitoring, logging improvements, and pipeline reliability.
- Collaborate with analytics teams to ensure accurate reporting datasets.
- Participate in code reviews, documentation, and engineering best practices.
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What This Job Offers
Career Level
Mid Level
Education Level
No Education Listed
