arbor - Data Engineering
Requirements
• 3–6+ years of experience in a data engineering or analytics engineering role, ideally at a high-growth startup or in a domain involving complex, real-time data (energy, fintech, marketplace, or similar). • Strong dbt fundamentals — you know how to design models that are maintainable, not just functional. You think about testing, documentation, and downstream consumers as part of the job, not afterthoughts. Solid SQL is a given; Python for pipeline development or data quality tooling is a plus. • Hands-on experience with Snowflake, including schema design, query performance, and understanding the cost/performance tradeoffs of how data is structured and accessed. Comfort with GCP data services (BigQuery, Cloud Storage, Pub/Sub) is a plus given our infrastructure footprint. • Experience building dashboards for business stakeholders in tools like Hex, Looker, or similar. You know the difference between a dashboard that gets used and one that doesn't. • Energy markets or regulated industry experience is not required, but genuine curiosity about how electricity pricing, competitive markets, and the grid work will make this role more interesting to you. • An AI-native approach to your own productivity — you're actively using AI tools to accelerate development and aren't waiting for someone to tell you to start. • Compensation & Work Setup Competitive salary + meaningful equity + benefits. We're flexible on location but value regular in-person collaboration with the team.
Responsibilities
• Build and maintain our data pipeline infrastructure, spanning ingestion through Fivetran and custom pipelines from our GCP production systems into Snowflake. You'll own our dbt transformation layer end-to-end — modeling energy market data, customer lifecycle events, marketplace results, and utility rate feeds into clean, reliable, and well-documented data assets. • You'll partner closely with engineering, operations, and leadership to deliver analytics that directly inform business decisions — rate monitoring, supplier pricing trends, customer switching patterns, and marketplace performance. You'll work in Hex to build and maintain dashboards that surface actionable intelligence for non-technical stakeholders, and you'll help define data contracts and schema standards that make our Snowflake environment trustworthy as we scale. • You'll also play a meaningful role in shaping how we use AI in our data workflows — whether that's automating data quality monitoring, accelerating development with AI-assisted SQL and Python, or surfacing anomalies in complex regulatory data feeds.
Benefits
• What is an interesting data project you have worked on in the past 6 months? • Describe a dbt model or data pipeline you built that you're proud of. What problem did it solve, and what would you do differently today? • How are you currently using AI tools in your data work, and what's a specific example where it meaningfully changed how you approached a problem?
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