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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # first in-house Data Engineer - **Company:** Atticus, Inc. - **Location:** Los Angeles, CA, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Query Performance, Airflow, BigQuery, Information Engineering, Data Infrastructure, Data Systems, Data Warehousing, Database Queries, Python (Programming Language), DataOps, Data Pipelines, Golang - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/lead-data-engineer-atticus-7995702 ## About the Role * 4+ years of professional experience in data engineering, ideally at a high-growth startup or fast-moving team within a larger organization * Hands-on experience with the modern data stack - proficiency with BigQuery (or a comparable cloud warehouse), dbt, and an orchestration tool like Dagster or Airflow * Strong SQL skills and fluency in Golang, Python, or another common Data Engineering language * Track record of improving or modernizing data systems iteratively - you're comfortable inheriting legacy infrastructure and systems and making them progressively better * Strong communication and collaboration skills - able to work fluidly across both technical and business-oriented teams Bonus / Nice-to-Have: * Experience transitioning data infrastructure from an outsourced or contractor model to an in-house team * Familiarity with data observability tools * Experience supporting or collaborating with a data science function, including ML feature pipelines We are strongly committed to building a diverse team. If you're from a background that's underrepresented in tech, we'd love to meet you., This job is fully remote and we're committed to empowering everyone with flexibility. Work remotely, and travel to LA (on the company dime) as needed to be with your colleagues - usually quarterly, plus offsites. We care a lot about building a great culture and we think some interactions need to happen in person, so we put a lot of thought into retreats, offsites, and other ways to gather. ## Description We are looking for our first in-house Data Engineer to own and evolve our core data infrastructure. This is an early and high-impact role. As the data engineering function grows under Engineering, you'll have a real voice in shaping how it's built - the processes, standards, and team culture. You'll sit at the intersection of our Engineering and Business Operations teams, which means you'll spend your time both building reliable, scalable systems and translating business needs into well-designed data products. You'll work closely with data scientists, business analysts, and product leaders to make sure our data is clean, accessible, and trustworthy. What You'll Do * Own and operate our data warehouse, pipelines, and transformation layer * Design, build, and maintain scalable, reliable data pipelines that ingest data from across our platform and third-party sources, ensuring data is always available and trustworthy for downstream consumers * Partner with data scientists and analysts to deliver clean, well-documented datasets and optimize query performance so teams spend less time wrangling data and more time generating insights * Incrementally improve and modernize our existing data systems - you won't build everything from scratch, but you'll know how to assess what we have, prioritize what matters, and migrate thoughtfully * Implement data quality monitoring, alerting, and documentation practices that build trust across the organization The role is a rare opportunity to join a fast-growing Series C startup that doubles as a B-corp social enterprise. Every project you take on will help clients in need get the help they deserve, and you'll shape our company culture as we scale. We're looking for data scientists who are excited about our mission and the challenges it entails. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Scoring 2000 Products per Request: Performance Pitfalls in Golang](https://www.wearedevelopers.com/videos/2073-scoring-2000-products-per-request-performance-pitfalls-in-golang) ## Related Articles - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 150 - The shift to AI generated code, fingerprinting and OKRs vs. doing your job](https://www.wearedevelopers.com/magazine/533-dev-digest-150-the-shift-to-ai-generated-code-fingerprinting-and-okrs-vs-doing-your-job)