Data Engineer
Sigma Computing is hiring a Data Engineer in San Francisco, United States. It pays $140k-$180k a year and Level rates it ; you can apply on Sigma Computing.
Level's read on this job
- On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
- The posting mentions Databricks, Snowflake and Fivetran among its tools and skills.
- Level classes it as a mid-level role.
- Sigma Computing has 76 other open roles on Level.
AI in this role
Builds and scales production data pipelines and infrastructure with a focus on data governance and terraform deployments.
Data Engineer, Data Platform
About the Role
We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects.
If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat!
What You Will Be Doing
- Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma (Tech we use: Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane)
- Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses
- Scale our terraform deployment across all of our Snowflake assets
- Continue to advance our data governance policies
- Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels
Qualifications We Need
- Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks)
- Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success.
- Experience deploying data governance frameworks with a scalable and repeatable process
- Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that
- 3+ years of relevant experience working in a data engineering role
- Startup experience
Qualifications We Want (also, skills you’ll learn!)
- A drive to continuously learn (and share those learnings) about the evolving data ecosystem
- Familiarity with dbt
- Advanced knowledge python knowledge
- Advanced knowledge and strong opinions around orchestrators (e.g., Astronomer, Airflow, Dagster)
- Advanced knowledge of working with public clouds (e.g., AWS, GCP)
Additional Job details
The base salary range for this position is $140k - $180k annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.
About us:
Sigma is the AI Apps and agentic analytics platform built on the cloud data warehouse. Business and technical teams use Sigma to explore live data, build intelligent applications, and automate critical workflows all without moving data or breaking governance. Sigma supports a spreadsheet interface, SQL, Python, and native AI in a single governed workspace, giving every team the speed to act and IT the control to scale. Sigma is trusted by more than 2,000 customers, including AMD, Duolingo, Colgate-Palmolive, and JPMorgan Chase.
Sigma announced its $80M in Series E financing in May 2026. The round was led by Princeville Capital, with new strategic investors Databricks Ventures, ServiceNow Ventures, and Workday Ventures participating alongside returning investors Altimeter Capital, Avenir Growth Capital, D1 Capital Partners, K5 Global, NewView Capital, Spark Capital, Sutter Hill Ventures, and XN. This milestone follows Sigma reaching $200M in annual recurring revenue in April 2026, with more than 100% year-over-year growth and 1.1 million new active users added in the latest fiscal year.
Come join us!
Benefits For Our Full-Time Employees:
- Equity
- Generous health benefits
- Flexible time off policy. Take the time off you need!
- Paid bonding time for all new parents
- Traditional and Roth 401k
- Commuter and FSA benefits
- Lunch Program
- Dog friendly office
Sigma is an equal opportunity employer. We are committed to building a smart and strong team regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, veteran, or any other protected status. We look forward to learning how your experience can enable all of us to grow.
Note: We have an in-office work environment in all our offices in SF, NYC, London and Sydney. All roles have a 25% travel expectation unless explicitly stated otherwise.
Our Privacy Practices
When you submit a job application on this site, Sigma processes your personal data for the purposes of evaluating your candidacy for employment at Sigma and as otherwise needed throughout the recruitment and hiring process. Please review Sigma’s Candidate Privacy Notice for more details. Please note that your personal data may be transferred to a country other than the one in which it was provided (including to the USA, the UK, and Canada, Australia).
Sigma’s use of AI
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
How we rate this
Data Engineer at Sigma Computing rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- This job starts at
- $140k
- Typical data engineer job
- $150k
This posting starts 7% below the typical data engineer job. See data engineer jobs
Questions you could be asked
- What's a project where you used Databricks hands-on?
- Walk me through how you've used Snowflake in your day-to-day work.
- What are the limits of Fivetran that you've run into, and how did you work around them?
- What's a project where you used Dagster hands-on?
- Walk me through how you've used Dlt in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Databricks, Snowflake, Fivetran, Dagster, and Dlt. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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