Member of Technical Staff, Data
Join Fireworks AI as an Analytics Engineer to own data domains and build impactful analytics solutions for various business functions.
Posted by employer 1 month ago
First seen on Joblaze 1 month ago
Last verified on the company career page 23 hours ago
What you'll build
- Own your function's data domain end to end
- Build and maintain pipelines in BigQuery and Coalesce
- Establish authoritative models for your domain
- Build dashboards for business operations
- Automate manual processes
Must have
- 5+ years in data analysis, analytics engineering, and/or data engineering
- Strong SQL proficiency
- Strong visualization proficiency
- Working knowledge of data engineering
- Strong analytical thinking
- Clear communication with non-technical partners
Nice to have
- Proficiency in Python for automation
- Experience building LLM-powered agents
- Experience with modern BI and transformation tooling
- Background in AI infrastructure or developer tools
- Depth in one of the specified domains
Requirements
- Experience
- 5+ years
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In the role of Analytics Engineer at Fireworks AI, the individual will manage data domains specific to various business functions, ensuring accurate measurement and reporting. Proficiency in SQL, data visualization, and a solid understanding of data engineering are essential, along with experience in Python for automation. This position is ideal for seasoned professionals with a background in data analysis or engineering, particularly those familiar with AI infrastructure or usage-based platforms. The team operates in a collaborative environment, emphasizing ownership and direct impact on business operations.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 20, 2026. Last confirmed on Fireworks AI's careers page November 8, 2026.
- Python appears in 70.3% of 74 comparable mid data engineering roles in United States; Sigma appears in 4.1% of 74 comparable mid data engineering roles in United States.
Quick facts
- How much experience is required?
- At least 5 years of relevant experience for this Member of Technical Staff, Data role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: BigQuery, Coalesce, Git, Python, Sigma.
- What seniority level is this role?
- Fireworks AI targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff, Data role at Fireworks AI.
From the original posting
THE ROLE
We are seeking a Member of Technical Staff, Data to build business-critical data pipelines as our data platform scales. Our business teams need data for analytics, experimentation, and forecasting to support Fireworks’ growth. You will partner with these business teams and with our data platform engineers to design thoughtful data models, engineer the pipelines, put them in production, and ensure they give consumers the data they need to act decisively.
You’re a good fit for this role if you enjoy operating highly autonomously, if your working style stresses both efficiency and correctness, and if you love bringing structure to complex and messy questions.
WHAT WE'RE LOOKING FOR
Required
5+ years in data engineering or similar roles.
Strong proficiency in SQL both for querying and for writing pipeline jobs.
Experience translating business needs into clear metrics, dimensions, and a data model.
Hands-on experience building and maintaining production data pipelines.
Excellent communication with senior level stakeholders, technical and non-technical.
Demonstrated autonomy in an environment with open ended problems.
Availability to work in office in San Mateo 3x days per week.
Preferred
Proficiency in Python or similar languages.
Experience with Google BigQuery.
Experience working with dbt, Coalesce, Airflow, or similar.
Experience using a data quality or observability tool (Bigeye, Monte Carlo, Great Expectations, or similar).
Why Fireworks?
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Standard company text repeated across Fireworks AI's postings is omitted here.