Job description

About the Team: Grindr is an AI-native platform powering how millions of gay people connect globally. With 15M+ monthly users, 130B+ annual messages, and a team of fewer than 200, we move fast, stay lean, and tackle technical problems at a scale few companies ever see. The Data Engineering team turns raw product data into the trusted datasets that power decisions across Grindr, from dashboards and experimentation to machine learning models and features in the app itself. And we’re pushing that further than most. Every company wants an AI-powered data analyst; we’ve already built one. Data Daddy is our production AI analyst, used daily in Slack by employees and senior leadership to answer real business questions, with visibility all the way up to our CEO. It’s only as good as the data behind it, and that’s where this team comes in. 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. This is a hybrid role based in our Chicago, SF, or Palo Alto office and will require you to be in person Tuesdays and Thursdays. About the Job: - 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. Role Requirements: - Analytics Engineering Fundamentals: Strong SQL skills and experience designing dimensional data models, defining business metrics, and building datasets that support complex analytical questions. - 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. - 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. - Cross-Functional Collaboration: Experience working with Data Scientists, ML Engineers, analysts, and business stakeholders to understand requirements and deliver reliable data products. - AI-Native Development: Experience using agentic coding tools (Cursor, Codex, Claude Code or similar) as a core part of your daily work. You May Thrive in this Role if You: - Have experience working with Snowflake, Airflow, dbt, or comparable data transformation and orchestration technologies. - Have built or contributed to semantic layers using tools such as Looker, dbt Semantic Layer, or similar frameworks. - Are interested in how LLMs and AI agents can transform the way organizations discover, understand, and analyze data. - Enjoy taking ownership of ambiguous problems, working directly with stakeholders, and building solutions that have measurable business impact. Benefits and Perks: - Health, Dental & Vision Full premium coverage for you. Partial coverage for dependents. - Family Formation Up to $300,000 in fertility and family-building support, covering IVF, surrogacy, egg freezing, and adoption. - Retirement: 401(k) with 6% match and immediate vesting. - Compensation: Industry-competitive compensation, company bonus, and equity for every employee. - Gender-Affirming Care : Industry-leading gender-affirming offerings with up to 90% cost coverage, access to Included Health, monthly stipends for HRT, and more. - Time Off & Rest Flexible vacation policy. Two company-wide rest weeks per year. - Other Benefits: Monthly stipends for cell phone, internet, wellness, food, and commuting, breakfast/lunch About Grindr: Grindr is building the Global Gayborhood in your Pocket. With more than 15 million monthly active users, Grindr has become a fundamental part of the gay community and is charting a path to make the world more free, equal, and just. As a public company, we're moving into the next chapter: becoming an AI-native organization that's redefining what's possible for our community. We're embedding AI into our product and operations, moving with startup speed while operating at scale. Everything we do is rooted in impact for our users and outcomes for the business. This isn't social work, it’s impact through excellence. Business success is what gives us the power to serve our community and the seat at tables others can't reach. How we work is defined by Grindr Mode, our operating model that's moderately hardcore day-to-day and truly hardcore when it counts. We think like owners, drive real outcomes, create clarity through action, and push each other to go further than we thought possible. We’re headquartered in West Hollywood with offices in the Bay Area, Chicago, and New York. Our work extends beyond the product through Grindr for Equality, our social impact initiative that's partnered with 100+ community organizations globally to advance safety, health, and human rights for LGBTQ+ people worldwide. We're profitable, growing, and building a team of smart, driven people who bring different backgrounds, experiences, and perspectives to the work. Want to build technology at a massive scale that serves millions? Come join us! Grindr is an equal-opportunity employer. To learn more about how we handle the personal data of applicants, visit our Employee and Candidate Privacy Policy grindr.com.

Requirements

Must-haves

The Data Engineering team turns raw product data into the trusted datasets that power decisions across Grindr, from dashboards and experimentation to machine learning models and features in the app itself.
This is a hybrid role based in our Chicago, SF, or Palo Alto office and will require you to be in person Tuesdays and Thursdays.
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.
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.
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.
Cross-Functional Collaboration: Experience working with Data Scientists, ML Engineers, analysts, and business stakeholders to understand requirements and deliver reliable data products.
AI-Native Development: Experience using agentic coding tools (Cursor, Codex, Claude Code or similar) as a core part of your daily work.
You May Thrive in this Role if You:
Have experience working with Snowflake, Airflow, dbt, or comparable data transformation and orchestration technologies.
Have built or contributed to semantic layers using tools such as Looker, dbt Semantic Layer, or similar frameworks.
Are interested in how LLMs and AI agents can transform the way organizations discover, understand, and analyze data.
Enjoy taking ownership of ambiguous problems, working directly with stakeholders, and building solutions that have measurable business impact.

Nice-to-haves

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Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Wellness