Post a Job
Post a role →
HOME Data Engineering & Architecture Data Engineer - 1668
  • AKube Inc
  • Santa Monica, CA
  • Contract
  • <48 Hours
AKube Inc VERIFIED EMPLOYER

Data Engineer - 1668.

Data Engineering & Architecture Contract
♡ Save to shortlist
??% CV Match
Sign in to upload a CV and see how you match

Data Engineer - 1668: our view in 3 lines...

  • The Role:This role is for a data engineer who builds and maintains data pipelines and datasets used for marketing acquisition reporting.
  • The Person:The person will build and maintain ETL/ELT pipelines using Databricks, PySpark, and SQL for marketing acquisition reporting, migrate Snowflake SQL scripts into Databricks Unity Catalog, and build ingestion pipelines for external marketing vendor data.
  • Requirements:The ideal candidate has 4+ years of Data Engineering experience, strong SQL skills, PySpark or Spark SQL, Databricks, Delta Lake, Unity Catalog, and AWS services such as S3, IAM, EC2 and Glue.

About the role

City:  Santa Monica, CA/ Burbank, CA or Glendale, CA
Onsite / Hybrid / Remote: Hybrid. Onsite Monday through Thursday. Remote Friday.
Duration: 6 months - Contract to Hire
Rate Range: Up to $92.50/hr on w2
Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B

Must Have:

  • 4+ years of Data Engineering experience.

  • Strong SQL skills, including complex joins, window functions, and analytical queries.

  • Hands-on production experience with PySpark and/or Spark SQL.

  • Databricks experience, including Delta Lake and Unity Catalog.

  • Strong understanding of ETL/ELT pipelines, data modeling, and distributed processing.

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.

Qualifications:

  • Minimum 4 years of professional Data Engineering experience or equivalent.

  • Experience building production pipelines in Databricks.

  • 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.

Nice to Have:

  • 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.

Published November 4, 2026
Location Santa Monica, CA
Category Data Engineering & Architecture  
Job Type Contract  

Read our Cookie Policy