Data Engineer - 1668

aKube • Santa Monica, CA

1d • Hybrid

About The Position

The Data Engineer will develop and maintain ETL/ELT pipelines for marketing acquisition reporting using Databricks, PySpark, and SQL. The role includes migrating Snowflake SQL scripts and transformations into Databricks Unity Catalog and building ingestion pipelines for external marketing vendor data. The engineer will parse, normalize, transform, and validate data, implement data quality checks and monitoring alerts, and resolve pipeline issues. The position also supports SLA monitoring, logging improvements, pipeline reliability, and accurate reporting datasets in collaboration with analytics teams. The engineer will participate in code reviews, documentation, and engineering best practices.

This is a six-month contract-to-hire position based in Santa Monica, Burbank, or Glendale, California. The work arrangement is hybrid, with onsite work Monday through Thursday and remote work Friday. The rate is up to $92.50 per hour on W-2.

Requirements

• At least 4 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 Delta Lake, Unity Catalog, 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.
• Work authorization: Green Card, U.S. citizen, or valid EAD other than OPT or CPT; H-1B is not accepted.

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.
• Parse, normalize, transform, and validate data.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed