PostHog: Product Engineer - Data Modeling
Role highlights
Full Time
Permanent
Mid
Remote
This mid-level Product Engineer role at PostHog focuses on data modeling within a robust data stack environment. The ideal candidate has strong backend engineering skills with proficiency in Python, including asynchronous programming, and experience with Temporal.io is advantageous. Expertise in container orchestration and deployment is required, specifically with Kubernetes and Docker, alongside scalable object storage solutions like S3. The role demands solid understanding and hands-on experience with building resilient, stateful, asynchronous data workflows, including debugging and monitoring using observability best practices such as logging and testing. Familiarity with Directed Acyclic Graphs (DAGs) and batch processing is essential, and experience with dbt is a plus. Additionally, the candidate should be comfortable developing user interfaces for data-intensive tools using React, bridging frontend and backend responsibilities. The position requires autonomy, proactive problem-solving, and the ability to deliver results in a fast-paced, product-led, open-source company environment. A bachelor's degree and approximately 50 experience points indicate a well-educated professional with a solid track record. The role offers high autonomy and the opportunity to contribute to core platform products that support both internal teams and external users, emphasizing stability, scalability, and production readiness.
About the role
About PostHog
- Equips developers to build successful products
- Started with open-source product analytics (Y Combinator W20)
- Shipped over a dozen products: built-in data warehouse, customer data platform, Max AI (AI-powered analyst)
- Upcoming roadmap: messaging, customer analytics, AI task creation and coding, logs and support analytics
- Open source, product-led, well-funded, and "default alive"
- Values are based on real work, not just aspirations
Role Summary
- Join the Data Stack team as a Product Engineer - Data Modeling
- Build end-user tools for understanding and traversing data models
- Work on materializing user-defined queries and scheduling DAGs of query materialization
- Debug stateful data workflows using k8s pod metrics and schedule jobs with Temporal.io
- Contribute to a core product and foundational platform for both users and internal teams
- Push the boundaries of the Data Stack while ensuring stability and production readiness
Responsibilities
- Build resilient systems for data modeling and workflows
- Materialize and schedule user-defined queries
- Debug and monitor stateful, async data workflows
- Develop UIs for data-intensive tools (React)
- Work with DAGs and batch processing
- Collaborate with autonomy and proactively deliver results
Requirements
- Strong experience with Kubernetes, Docker, and S3 at scale
- Proficient in Python (async-python and Temporal.io skills are a plus)
- Good practices in logging, testing, and monitoring (observability)
- Comfortable debugging stateful, async data workflows
- Experience building UIs for data-intensive tools (React)
- Experience with DAGs and batch processing (Dbt experience is a plus)
- Strong backend skills for complex systems
- Proactive, autonomous, and results-driven
Benefits
- High autonomy and opportunity to do the best work of your career
- Well-funded company with a strong team and global distribution
- Commitment to a fair and accessible interview process (accommodations available)
How to Apply
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