Senior Data Platform Engineer

Build the Data Platform That Powers What's Next.

We're seeking a seasoned Senior Data Platform Engineer to design and operate the pipelines, services, and data products that the rest of the company builds on.

In this role, you'll own the flow of data end to end -- ingesting and transforming it through ETL/ELT and dbt, orchestrating reliable batch and streaming workflows, and exposing it through the APIs and microservices that product teams depend on, including the next generation of features powered by large language models (LLMs) and machine learning.

Beyond hands-on engineering, you'll shape technical direction, mentor teammates, and help drive standardization across the department.

If you're energized by building dependable data systems and excited to apply LLMs and ML to real product problems, we'd love to have you on the team.

We are seeking an experienced Senior Data Platform Engineer to join our data team in building and maintaining a robust data platform and the backend services around it, while providing technical guidance and mentorship.

This role focuses on designing and shipping high-quality data pipelines and transformations -- building and maintaining ETL/ELT and dbt workflows, orchestration, and data-quality and observability practices -- alongside the Python microservices and APIs that serve data and integrate LLM and ML capabilities into production.

You'll also contribute to technical direction at the team level and lead standardization efforts across the department, collaborating closely with product teams and stakeholders to deliver reliable, scalable, and well-documented data and backend systems.

Responsibilities: Technical Collaboration Contribute to technical direction and strategic planning at the team level.

Evaluate and recommend new technologies and approaches for backend and AI/ML evolution.

Provide technical guidance and code reviews for team members.

Provide technical guidance and support to product teams consuming backend services.

Data Pipelines, ETL & Transformation Design, build, and maintain data pipelines and ETL/ELT workflows that ingest, move, and transform data across source systems, the warehouse, and downstream consumers.

Develop and maintain dbt models, tests, and documentation to support analytics, reporting, and product features.

Build and operate workflow orchestration for batch and streaming data (scheduling, dependency management, retries, and alerting).

Establish and enforce data quality, reliability, and observability practices across pipelines (monitoring, lineage, freshness, and validation).

Implement schema management, versioning, and migration patterns to evolve data models safely.

Optimize pipeline performance, cost, and scalability across the data platform.

Data Application Development & Maintenance Design, develop, and maintain microservices in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.

Design and build APIs and services that integrate LLMs and ML models -- includi...