Remote Senior Data Engineer

Hello, we’re Instrumentl. ? We're a mission-driven startup helping the nonprofit sector to drive impact, and we're well on our way to becoming the #1 most-loved grant discovery and management tool. To get there, we're hiring a Senior Data Engineer to help us scale and evolve our data platform, which is in its early stages.

About us: Instrumentl is a hypergrowth YC-backed startup with over 5,500 nonprofit clients, from local homeless shelters to larger organizations like the San Diego Zoo and the University of Alaska. We are building the future of fundraising automation, helping nonprofits to discover, track, and manage grants efficiently through our SaaS platform. Our charts are dramatically up-and-to-the-right ? — we’re cash flow positive and doubling year-over-year, with customers who love us (NPS is 65+ and Ellis PMF survey is 60+).

Join us on this rocket ship! About the role: As a Senior Data Engineer at Instrumentl, you’ll play a key role in shaping the architecture, improving reliability, and building the systems that power data across the company. This is a high-impact opportunity to bring structure and scalability to an existing foundation—ideal for someone who enjoys high ownership, thrives in ambiguity, and wants to have a lasting impact on foundational infrastructure.

You’ll partner closely with our engineering, product, and business teams to design and implement scalable systems for data ingestion, storage, processing, and analytics. Get to know us at instrumentl.com/about ! The Instrumentl team is fully distributed (though if you’d like to work from our Oakland office, we would love to see you there).

For this position, we are looking for candidates based in the United States who have significant overlap with Pacific Time Zone working hours. What you'll do: Design and scale our data platform, including pipelines, models, and orchestration frameworks Develop scalable ETL/ELT pipelines for ingesting data from APIs, databases, and event streams Define and implement systems for data ingestion, storage, processing, and transformation Build and manage workflow orchestration using tools like Airflow Build semantic layer as well as dashboards Establish best practices for data modeling, testing, and quality Partner with stakeholders to shape data requirements and enable BI and analytics use cases Apply software engineering principles (testing, CI/CD, modular design) to data infrastructure Optimize systems for performance, scalability, and cost from day one What you bring: A minimum of 5+ years as a software engineer, with the last 2-3 years in data engineering; experience in early-stage or 0→1 environments is a plus Strong programming skills in Python Advanced proficiency in SQL Proven experience building ETL/ELT pipelines end-to-end Experience with orchestration tools like Airflow Deep understanding of the data lifecycle: ingestion → storage → processing → transformation → serving Experience with cloud platforms ( AWS, GCP, or Azure ) Experience supporting BI tools ( Looker, Tableau, etc. ) Familiarity with modern data warehouses ( Snowflake, BigQuery, Redshift ) Nice to have: Experience working in startup environments Experience with data analytics and data science concepts Experience with streaming pipelines ( Kafka, Kinesis ) Exposure to ML/AI data pipelines Familiarity with Ruby and Rails What success looks like: A scalable, reliable data foundation Clear, well-documented data models used across teams A data platform that is flexible and ready to scale with company growth Stakeholders have trusted, accessible data for decision-making Compensation