Data Warehouse Engineer

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

$130K-$170K From the posting source checked Jun 20, 2026

401(k) match

Not verified

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

29% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Warehouse Engineer San Francisco About the Role Together AI is building high-performance inference compute and the software platform around it. We're looking for an early-career Data Warehouse Engineer with strong fundamentals and high growth potential to grow into a technical lead over time. You'll contribute to designing and operating our data warehouse, ETL pipelines and orchestration, work on core data models and metrics, and help raise the bar on data quality and governance across the org - with mentorship and support from experienced engineers. Requirements - 0-4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering. - Solid SQL fundamentals - you're comfortable writing queries and have some exposure to window functions or dimensional modeling concepts. - Some hands-on experience with dbt or Airflow, or strong eagerness to learn - coursework and personal projects count. - Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus. - Familiarity with data modeling concepts like SCD2 or star schemas - even if only from coursework. - Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs. - High standards for data quality, reliability, and maintainability - you care about getting things right. Responsibilities - Contribute to building and maintaining a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data. - Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented). - Help design analytics-ready models:

Read the full description at job-boards.greenhouse.io. FewerJobs shows a preview and links to the original posting.