Senior Data Engineer, Analytics

Grindr • Chicago, IL

1d • Hybrid

About The Position

Grindr is hiring a Senior Data Engineer, Analytics to own data for its newest product features. The role is part of the Data Engineering team, which turns raw product data into trusted datasets used for dashboards, experimentation, machine learning models, product features, and the company’s AI analyst, Data Daddy.

The engineer will take end-to-end ownership of critical business datasets, from understanding stakeholder requirements and designing data models to building pipelines, validating metrics, and maintaining data quality. The role also involves creating reliable, AI-ready analytics models and reusable semantic definitions so that employees, analysts, and AI agents can consistently discover and use business data.

The position partners closely with Data Science, ML Engineering, Product, Analytics, and business stakeholders to deliver scalable data solutions for decision-making, experimentation, and machine learning. The team uses modern data engineering practices and AI-assisted development tools. This is a hybrid role based in Grindr’s Chicago, San Francisco, or Palo Alto office, with in-person work required Tuesdays and Thursdays.

Requirements

• Strong SQL skills.
• Experience designing dimensional data models, defining business metrics, and building datasets for complex analytical questions.
• Experience turning raw, high-volume event data into reliable production datasets.
• Experience applying business logic, building and maintaining transformations, and validating data quality in a modern cloud warehouse.
• Experience with orchestration tools such as Airflow.
• Understanding of semantic layers, metric definitions, and structuring data so business logic is reusable, consistent, and interpretable across datasets.
• Experience collaborating with Data Scientists, ML Engineers, analysts, and business stakeholders to understand requirements and deliver reliable data products.
• Experience using agentic coding tools such as Cursor, Codex, Claude Code, or similar as a core part of daily work.

Nice To Haves

• Experience with Snowflake, Airflow, dbt, or comparable data transformation and orchestration technologies.
• Experience building or contributing to semantic layers using Looker, dbt Semantic Layer, or similar frameworks.
• Interest in how LLMs and AI agents can transform organizational data discovery, understanding, and analysis.
• Enjoyment of taking ownership of ambiguous problems, working directly with stakeholders, and building solutions with measurable business impact.

Responsibilities

• Own critical business datasets end to end, including understanding stakeholder requirements, designing data models, building pipelines, validating metrics, and ensuring data quality.
• Develop reliable, well-structured data models for analytics, reporting, and AI-driven tools such as Data Daddy.
• Create and maintain reusable metrics, dimensional models, and semantic definitions.
• Partner with Data Science, ML Engineering, Product, Analytics, and business stakeholders to translate business questions into scalable data solutions.
• Build data solutions that support decision-making, experimentation, and machine learning.
• Use AI-assisted development tools and modern data engineering practices to improve development, data modeling, testing, and documentation.

Benefits

• Full premium coverage for employee health, dental, and vision insurance; partial dependent coverage.
• Up to $300,000 in fertility and family-building support, including IVF, surrogacy, egg freezing, and adoption.
• 401(k) with 6% company match and immediate vesting.
• Industry-competitive compensation, company bonus, and equity for every employee.
• Gender-affirming care offerings with up to 90% cost coverage, access to Included Health, and monthly stipends for HRT.
• Flexible vacation policy.
• Two company-wide rest weeks per year.
• Monthly stipends for cell phone, internet, wellness, food, and commuting.
• Breakfast and lunch.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed