Performance Marketing Data Engineer | AI-Driven Pipelines

UNAVAILABLE; Simi Hills (CA); Hybrid; USD 88,540 - 135,632; Full time

Benefits offered by this job

401K matching

Wellness program

Medical, dental, and vision coverage

Hybrid work arrangements

Parental bonding leave

Employee discount program

Paid holidays

Flexible time off

Job summary

CJ is seeking a Data Engineer to design, build, and maintain scalable data platforms and pipelines supporting analytics, AI/ML, and enterprise data products. You will work across Databricks, AWS, Snowflake, and Google Cloud, building Lakehouse architectures and Medallion patterns.

Collaborate with Data Science, Analytics, Product, and Engineering teams; maintain CI/CD, source control, and deployment best practices; design monitoring dashboards and ensure data quality.

Qualifications

• 3–5 years of experience in Data Engineering or analytics engineering.
• Experience with cloud-based data platforms (Databricks, AWS, Snowflake, GCP).
• Familiarity with AI/automation tools to improve code quality and productivity.
• Strong SQL and Python skills; Spark/PySpark experience preferred.
• Experience with ETL/ELT pipelines and data lakehouse concepts.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL and Spark technologies.
• Build data ingestion frameworks via APIs, SFTP, cloud storage, and databases.
• Develop data products within a modern Data Lakehouse architecture following Medallion design.
• Create and optimize data workflows, orchestration, and monitoring for reliability and performance.
• Manage cloud-based data infrastructure across Databricks, AWS, Snowflake and GCP.
• Collaborate with Data Science, Analytics, Product, and Engineering teams to deliver scalable data assets.

Skills

SQL

Python

Spark

Tools

Databricks

AWS

Snowflake

Google Cloud

Job description

CJ is seeking a Data Engineer to design, build, and maintain scalable data platforms and pipelines supporting analytics, AI/ML, and enterprise data products. You will work across Databricks, AWS, Snowflake, and Google Cloud, building Lakehouse architectures and Medallion patterns.

Collaborate with Data Science, Analytics, Product, and Engineering teams; maintain CI/CD, source control, and deployment best practices; design monitoring dashboards and ensure data quality.