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HarveyHarveySan Francisco, CA

Senior Analytics Engineer, Product

The Senior Analytics Engineer will build product event data models, pipelines, and semantic layers that enable reliable self-serve analytics. The role requires 5+ years of relevant experience, strong SQL, dbt, Python, and Snowflake expertise, and close collaboration with Product, GTM, Finance, and executive stakeholders.

156k – 234k/yr
Hybrid5+ YOEData Engineering

About the role

Responsibilities

  • Design and build scalable data models and pipelines using dbt to transform raw data into reliable analytics assets.
  • Define and implement a semantic layer using tools such as LookML or Omni to standardize business metrics, dimensions, and data products.
  • Partner with Product, GTM, Finance, and executive stakeholders to deliver dashboards and analytical tools covering business health metrics.
  • Establish data modeling standards and best practices for accuracy, performance, usability, and maintainability.
  • Collaborate with Product Managers, Engineers, and Data teams on tracking plans for new product surfaces.
  • Own product event tracking strategy, including naming conventions, property schemas, identity resolution, sessionization, versioning, deprecation, and documentation.
  • Make analytical assets discoverable, reliable, and well documented.
  • Define taxonomy, governance, and modeling patterns for product event data, including user behavior, product usage, customer journeys, sessions, funnels, cohorts, and behavioral metrics.

Requirements

  • 5+ years of experience in Analytics Engineering, Data Engineering, Data Science, or a similar field.
  • Deep expertise in SQL, dbt, Python, and Snowflake.
  • Experience with modern business intelligence tools such as Looker or Omni.
  • Ability to define business and product metrics, uncover insights, and resolve data inconsistencies across complex systems.
  • Familiarity with version control using GitHub, CI/CD, and modern development workflows.
  • Experience modeling high-volume, semi-structured product event data, including JSON payloads, nested properties, user and account identifiers, sessions, funnels, cohorts, and behavioral metrics.
  • Experience with product analytics tools such as Mixpanel, Segment, or Amplitude.
  • Strong communication and cross-functional collaboration skills.
  • Comfort working through ambiguity in fast-moving environments.

Nice-to-haves

  • Experience at an early-stage, hyper-growth startup.
  • Experience with or knowledge of AI and LLMs.
  • Data engineering experience.
  • Experience managing a data warehouse, preferably Snowflake.
  • Experience at a world-class enterprise organization.

Compensation

  • $155,800–$233,600 USD, depending on location.

Skills

SQLdbtPythonSnowflakeLookeromniGitHubCI/CDJSONMixpanelsegmentAmplitudesemantic layerData ModelingProduct Analytics

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