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Senior Data Engineer (Analytics)

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Onsite

Senior Data Engineer (Analytics)

Grindr

Senior Data Engineer (Analytics)

Skills

SQL QueriesLookerData EngineeringData ScienceSnowflakeData AnalysisMachine LearningAIdbtApache Airflow

5 days ago

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Important information


Contract type:

Permanent

Salary:

$127,577 – $182,616 / year

Location:

United States

Work mode:

Onsite

Published on:

16 October 2026

What they need


  • We’re looking for a Senior Data Engineer, Analytics to own data for our newest product features: building the data models, metrics, and semantic layers that data scientists, ML engineers, and Data Daddy all rely on
  • You’ll partner closely with stakeholders across the business and help shape how data is used across the organization
  • At Grindr, we operate in Grindr Mode
  • Moderately hardcore day to day, truly hardcore when it counts
  • It’s about doing great work without burning out
  • Outcomes over outputs
  • Smart, driven people who raise your bar, with room to live full lives
  • Own Our Newest Features: Take end-to-end ownership of critical business datasets, from understanding stakeholder requirements and designing data models to building pipelines, validating metrics, and ensuring data quality
  • Build AI-Ready Analytics: Design and develop reliable, well-structured data models that power analytics, reporting, and AI-driven tools like Data Daddy, enabling employees to ask complex business questions using natural language
  • Develop the Semantic Layer: Create and maintain reusable metrics, dimensional models, and semantic definitions that make data consistent, discoverable, and accessible to both human analysts and AI agents
  • Partner Across Teams: Work closely with Data Science, ML Engineering, Product, and Analytics to translate business questions into scalable data solutions that support decision-making, experimentation, and machine learning
  • Leverage Modern Engineering Tools: Use AI-assisted development tools and modern data engineering practices to accelerate development and raise the bar on how we model, test, and document data

Benefits

  • 100% employer-paid medical, dental, and vision premiums for employees
  • 401k Matching (up to 6%)
  • Flexible PTO, sick-time, holidays, and two company wide shut-down weeks + an annual travel and leisure stipend
  • Equity for all employees
  • Monthly lifestyle stipend for food and wellness as well as fully catered onsite breakfast, lunch, and snacks
  • Gender Affirmation Fund for transgender and gender non-conforming employees
  • Queer-inclusive health benefits including LGBTQ consultative healthcare and expanded HRT shipped directly to employees in eligible states
  • Monthly commuter stipend to get you to and from the office on in-person collaboration days
  • Community projects and charitable giving stipend to support LGBTQ+ non-profit organizations alongside Grindr for Equality- Cross-Functional Collaboration: Experience working with Data Scientists, ML Engineers, analysts, and business stakeholders to understand requirements and deliver reliable data products
  • Analytics Engineering Fundamentals: Strong SQL skills and experience designing dimensional data models, defining business metrics, and building datasets that support complex analytical questions
  • Semantic Modeling: Understanding of semantic layers, metric definitions, and how to structure data so that business logic is reusable, consistent, and interpretable across multiple datasets
  • AI-Native Development: Experience using agentic coding tools (Cursor, Codex, Claude Code or similar) as a core part of your daily work
  • Data Engineering Experience: Experience turning raw, high-volume event data into reliable production datasets, including applying business logic, building and maintaining transformations, and validating data quality in a modern cloud warehouse with orchestration tools like Airflow
  • Have experience working with Snowflake, Airflow, dbt, or comparable data transformation and orchestration technologies
  • Enjoy taking ownership of ambiguous problems, working directly with stakeholders, and building solutions that have measurable business impact
  • Are interested in how LLMs and AI agents can transform the way organizations discover, understand, and analyze data
  • Have built or contributed to semantic layers using tools such as Looker, dbt Semantic Layer, or similar frameworks

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