Grindr is looking to build an exceptional data engineering team with expertise in real-time streaming technologies to achieve high quality and reliability. This role is about shaping the platforms and tools that empower data scientists and machine learning engineers, focusing on creating a seamless development experience and ensuring reliable, scalable systems.
Requirements
- 10+ years of experience working with data at scale, with a strong focus on data platforms and developer experience.
- Expert in Python and SQL, with significant experience in distributed data systems.
- Hands-on experience with Airflow (must-have) and dbt (able to set up from scratch).
- Strong knowledge of Spark, Databricks, or other distributed computing platforms for ML training.
- Experience with AWS and cloud-native architectures.
- Background in software engineering with a transition into data engineering preferred - able to apply SWE rigor to data platform design.
- Demonstrated ability to enhance developer experience - for example, building holistic automated solutions rather than one-off tables or fixes.
Responsibilities
- Design, develop, and deliver scalable data platforms that enhance the developer experience for data scientists and ML engineers.
- Solve technical problems of the highest scope and complexity, influencing platform direction and architecture across teams.
- Connect tools and systems into cohesive, automated workflows that eliminate repetitive work and unlock faster experimentation.
- Lead implementation of core platform technologies like dbt (from the ground up), Airflow (critical), and distributed computing frameworks (Spark, Databricks, or similar).
- Drive adoption of long-term, scalable solutions instead of one-off fixes.
- Stay on top of new technologies through R&D and prototyping to continuously improve developer experience, scalability, and reliability.
- Ensure governance and compliance standards are met around data representation, storage, classification, and retention.
Other
- Provide mentorship for engineers on your team and across the org.
- Track record of mentorship and technical leadership at the organizational level.
- Work closely with Data Scientists, ML Engineers, SREs, and Product Managers to make sure platforms and APIs meet real user needs.
- Familiar with data governance, classification, retention, and compliance frameworks (SOC2, GDPR, CCPA).
- This is a hybrid role based in Chicago or our Bay Area (San Francisco or Palo Alto) offices and will require you to be in office Tuesdays and Thursdays.
