Senior Data Engineer

We’re looking for a Senior Data Engineer to help us shape how we collect, analyze, and act on data across our AI-powered coding platform. You’ll build scalable data infrastructure, design high-quality data models, help evaluate our agents, and make sure decision-makers have the insights they need — from engineers to product managers to the founder.

You’ll be joining a small but ambitious Data & Analytics team on the ground floor. This is a rare opportunity to set the foundation for analytics at a fast-moving AI company led by serial founder Andrew Filev (ex-Wrike), where your work directly impacts the future of how software is built.

What You’ll Do

1. Design and run A/B tests that help us move fast without guessing — you'll guide the team in making smart, data-informed choices, and build out best practices for experimentation that everyone can rely on.
2. Develop and implement standardized processes for tracking new analytical events;
3. Turn raw data into real insights — dig into product usage, agent performance, and user behavior to help teams understand what’s working, what’s not, and where to go next.
4. Level up our analytics game by improving our reporting systems and introducing new metrics that reflect how users experience our AI tools.
5. Build trust in our data with robust quality checks and validation processes.
6. Architect DWH data models, create and optimize SQL queries and data models for cross-layer DWH data transformation using DBT.

Tech Details

1. Our current toolkit includes Amplitude, GCS, BigQuery, DBT, and Python, but we’re not locked in. You’ll help shape the architecture and pick the right tools as we scale.
2. We work with massive, AI-specific data like prompts and user content — not just pageviews and clicks. There’s very little legacy, so you won’t spend your days untangling old pipelines. Instead, you’ll be laying the groundwork for a data platform that powers the future of AI development.

What You Bring

1. 5+ years of experience in data warehouse (DWH) development and data transformation workflows.
2. Strong SQL skills, including the ability to write and optimize complex queries.
3. A solid understanding of Data Governance and Data Quality best practices.
4. Experience building and maintaining data transformation workflows, with knowledge of ETL/ELT processes, batch, and streaming data processing.
5. Proficiency in Python for data-related tasks.
6. A passion for data-driven decision making and the ability to extract insights from complex datasets.
7. Readiness to take on both data engineering and analytics tasks as needed.

Nice to Have

1. Experience with DBT and BigQuery.
2. Experience with designing and analyzing A/B experiments.
3. Experience creating reports using any BI tool.
4. Experience with AI system analytics and evaluation.