Senior Data Engineer

Hello, we’re Instrumentl. 👋 Nonprofits do some of the most important work in the world, and most of them are still managing grants in spreadsheets. We're fixing that. Instrumentl is a profitable, hypergrowth, YC-backed SaaS platform building the operating system for grant-funded organizations. More than 5,500 nonprofits use Instrumentl to discover, track, and win grant funding, from local community organizations to the San Diego Zoo and the University of Alaska. Collectively they’ve moved over $1 billion through our platform. We're growing quickly, customers love us (check out our G2 reviews!), and we're hiring people who want to build something that matters. About the role: You'll be our Senior Data Engineer, reporting to engineering leadership and taking ownership of a data platform that is still in its early stages. This is a high-ownership, build-from-the-foundation seat: you'll shape the architecture, stand up reliable pipelines and trusted data models, and set the engineering standards that let our data scale with the company. If you want real ownership over foundational infrastructure at a profitable, fast-growing company, rather than maintaining someone else's system at a larger one, this is that role. What you'll do: Platform & ArchitectureDesign and scale our data platform across pipelines, models, and orchestrationDefine and implement systems for data ingestion, storage, processing, and transformationOptimize systems for performance, scalability, and cost from the start Pipelines & Engineering PracticesBuild scalable ETL/ELT pipelines that ingest from APIs, databases, and event streamsApply software engineering principles such as testing, CI/CD, and modular design to data infrastructureEstablish best practices for data modeling, testing, and quality Data Enablement & PartnershipBuild the semantic layer and dashboards that make data usable across the companyPartner with engineering, product, and business teams to shape data requirementsEnable trusted, accessible data for BI and analytics decision-making What you bring: Required5+ years building production software, with at least 2 to 3 of those focused on data engineeringStrong programming skills in Python and advanced proficiency in SQLProven experience building ETL/ELT pipelines end to end, from ingestion through servingHands-on experience with a cloud platform (AWS, GCP, or Azure) and a modern data warehouse (Snowflake, BigQuery, or Redshift) Nice to haveExperience with workflow orchestration tools like AirflowExperience supporting BI tools such as Looker or Tableau, and building semantic layers and dashboardsDeep fluency across the full data lifecycle: ingestion, storage, processing, transformation, and servingExperience in early-stage or 0-to-1 environmentsExperience with streaming pipelines such as Kafka or KinesisExposure to ML/AI data pipelines, data analytics, or data science conceptsFamiliarity with Ruby and Rails Compensation & Benefits: For US-based candidates, the target salary range for this role is $170,000 – $190,000 USD, plus equity. Final compensation is determined based on experience, skillset, scope of responsibility, interview performance, and geographic location. We’re committed to paying competitively and equitably. Benefits100% covered health, dental, and vision insurance for employees (50% for dependents)Generous PTO, including parental leave401(k)Company laptop and home-office stipendBi-annual company retreats Instrumentl is evolving rapidly. You’ll always have new challenges and opportunities to grow here. Instrumentl is an equal opportunity employer. We are committed to building an inclusive workplace and do not discriminate based on race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, genetic information, or any other legally protected status. We encourage candidates from all backgrounds to apply. If you need a reasonable accommodation during the application or interview process, please let us know. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.