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Data Analytics Engineer (Product)

🕒 6 days ago
BigqueryCoalescePythonSQL

📜 Description

  • Own your function's data domain end to end — define what should be measured, model it, and be accountable for the numbers.
  • Build and maintain pipelines in BigQuery and Coalesce, aligned with company data standards and governance requirements.
  • Establish authoritative models for your domain that reconcile against the company's certified account and revenue definitions.
  • Build dashboards that replace spreadsheet exports and one-off pulls, ensuring they are trustworthy for business operations.
  • Surface problems proactively, addressing variance, anomalies, and completeness gaps before stakeholders ask.
  • Automate repetitive tasks by building workflows that streamline reporting and operational handoffs.

🛠️ Requirements

  • 5+ years in data analysis, analytics engineering, and/or data engineering
  • Strong SQL proficiency — you can design a good schema, write your own queries, and not bog down the warehouse
  • Strong visualization proficiency — you can build your team the dashboards they need so they can leverage the data for efficient decision making
  • Working knowledge of data engineering — you already know how to put up a pull request, respond to code review feedback, etc.
  • Strong analytical thinking — you decompose ambiguous problems, find the root cause behind a number that moved, and turn a maybe into a defensible explanation
  • A bias toward building systems over managing processes — you treat recurring manual work as a problem to solve
  • Proficiency in Python for automation, data work, and integrations
  • Experience building LLM-powered agents or automation workflows on top of analytics — after the core numbers are hardened
  • Experience with modern BI and transformation tooling (Sigma, Looker, Tableau; dbt, Coalesce, or similar)
  • Background in AI infrastructure, developer tools, or usage-based platforms — token pricing, GPU-hour metering, model mix, and cost-per-request as first-class business metrics
Full job description

About Us:

Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.

THE ROLE

We are seeking the first Data Analytics Engineer at Fireworks who will support our product management team.

You will define canonical metrics that measure user behavior, product performance, system performance, and financial measures. You’ll ensure the metrics accurately measure what the business needs to know and that they are socialized and understood across teams and senior leaders. You will extend and improve our data model, write pipelines to compute metrics, and partner with the data platform team to put them into production following rigorous engineering standards.

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 science, product analytics, analytics engineering, or a combination.

  • Experience defining, analyzing, and aligning business users on shared metrics.

  • Experience building or working on production data pipelines, hands-on.

  • Proficiency in SQL, Python, or similar languages.

  • 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

  • Experience analyzing performance of self-service developer-facing products.

  • dbt, Coalesce, or a similar transformation framework in production — models, tests, docs, shared repo

  • Background in AI infrastructure including inference, GPU-hour metering, attributing revenue to mixed model use, etc.

Why Fireworks?

  • Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.

  • Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.

  • Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.

  • Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

As an Analytics Engineer, you will create and maintain data infrastructure and models, ensuring digital behavioral data is reliable and ready for analysis and AI use cases.

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