Office Location: Onsite 2 per month for onsite meetings, otherwise remote - commutable candidates to 2425 Olympic Blvd., Suite 6000 West, Santa Monica, CA - 90404.
Job Summary
Key Responsibilities
Develop, test, and deploy ETL pipelines across multiple data sources within an established ingestion framework
Build integrations with third-party tools, APIs, and services to ensure data is synchronized and accessible
Monitor data pipelines, troubleshoot failures, and resolve issues with guidance from a senior engineer
Build and maintain approximately 10 BI dashboards supporting 2-3 partner teams
Ensure dashboard accuracy, performance, usability, and retirement of outdated or unused reports
Write and maintain data tests, including source-level data quality checks
Contribute to data modeling and transformation logic in dbt
Respond to one-off business questions through a managed intake queue
Maintain clear documentation for pipelines, workflows, and dashboards
Participate actively in code reviews as both an author and reviewer
Skill Breakdown
60% Data pipeline / ETL engineering
25% BI dashboard development and maintenance
Remaining focus on documentation, ad hoc requests, testing, and collaboration
Required Qualifications
1-3 years of experience in data engineering, analytics engineering, or a closely related data-focused role
Strong SQL skills for querying, transforming, and validating data
Working knowledge of Python for data engineering tasks
Experience with BI tools such as Power BI, Tableau, Looker, Sigma, or similar
Familiarity with cloud data warehouses such as Snowflake or Redshift
Exposure to dbt or strong willingness to learn
Familiarity with Git/version control
Comfortable asking questions and interested in understanding business context behind the data
Preferred Qualifications
Experience with Snowflake Cortex
Exposure to low-code ETL/ingestion tools such as Fivetran
Experience with transformation frameworks such as dbt
Exposure to orchestration tools like Airflow
Familiarity with AWS services such as S3, Lambda, or SQS
Experience building API integrations
Data modeling experience through work, internship, or coursework
Industry experience is a plus
Ideal Candidate Profile
We're looking for someone who is technically solid in SQL and Python, excited to deepen their experience in data engineering, and motivated by mentorship and growth. This person should be comfortable owning dashboard work in addition to pipeline development and should value collaboration, curiosity, and team fit.
Numbers & Facts
Location
California, CA
Skills
AWS Lambdaunmatched
Amazon Simple Storage Service (S3)unmatched
Amazon Web Services (AWS)unmatched
Application Programming Interface (API)unmatched
Business Intelligenceunmatched
Business Intelligence Softwareunmatched
Cloud Computingunmatched
Code Reviewsunmatched
Data Analysisunmatched
Data Managementunmatched
Data Modelingunmatched
Data Qualityunmatched
Data Warehousingunmatched
Database Extract Transform and Load (ETL)unmatched