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Senior Data Platform Engineer at Alpaca. Location Information: North America. Senior Data Platform Engineer. Remote - Americas . Apply. Who We Are:. Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure . for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more.. Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 10 million brokerage accounts.. Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of opening financial services to everyone on the planet. We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it.. Alpaca is proudly backed by $400 million in funding from top-tier global investors including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Opera Tech Ventures, SBI Group, Derayah Financial, Unbound, Peak XV, Elefund, and Y Combinator.. Our Team Members:. We're a dynamic team of 400+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond!. We're searching for passionate individuals eager to contribute to Alpaca's rapid growth. If you align with our core values—Stay Curious, Have Empathy, and Be Accountable—and are ready to make a significant impact, we encourage you to apply.. About the team & role. The . Data Platform. team builds and operates the shared infrastructure that powers how data is stored, moved, and consumed across Alpaca. Our platform supports financial transactions, customer data, API and system events, enriched datasets, and third-party sources that power critical decisions and products for internal teams and external stakeholders. We process hundreds of millions of events each day and that scale continues to grow as Alpaca serves more customers and launches new products.. As a . Senior Data Platform Engineer. , you'll design, build, and operate reliable systems across Alpaca's data platform, from distributed query engines and lakehouse storage to streaming infrastructure, governance, and data serving. You'll also work closely with our AI and Data Science teams to enable agentic workflows and machine learning capabilities. As part of a small team, you'll contribute across multiple initiatives, own projects from design through production, and help shape the future of our platform.. Our team is 100% distributed and remote.. What you’ll do. Design, build, and operate core data platform infrastructure, including distributed query engines, lakehouse storage, orchestration, and streaming pipelines.. Contribute to regional platform deployments, building scalable and repeatable infrastructure using Kubernetes and infrastructure-as-code.. Develop real-time data processing, analytics, and alerting capabilities for operational and product use cases.. Partner with AI and Data Science teams on the platform foundations for agentic workflows, evaluations, and ML lifecycle tooling.. Evolve our data catalog, governance, and access controls so data is discoverable and properly governed.. Own platform reliability through observability, on-call participation, and operational improvements while collaborating with cross-functional teams.. Must-haves. 5+ years of experience in data infrastructure, platform engineering, or software engineering, with demonstrated end-to-end ownership of production systems.. Strong Python and SQL skills, with experience building reliable pipelines, services, or platform tooling.. Experience building or operating distributed data systems, such as query engines, lakehouses, or streaming platforms.. Experience operating cloud infrastructure using Kubernetes, infrastructure-as-code, and deployment automation.. Sound operational judgment, clear technical communication, and the ability to collaborate across engineering teams.. . Nice to Haves:. Experience with distributed query engines such as Trino, Presto, or Spark, and open table formats such as Apache Iceberg.. Experience with streaming and real-time data infrastructure such as Kafka, Redpanda, Flink, or Debezium.. Experience with AI and agent infrastructure, including MCP servers, retrieval systems, agent observability, or LLM evaluation.. Experience supporting ML infrastructure using technologies such as MLflow, Vertex AI, or similar platforms.. Experience with real-time analytics engines such as ClickHouse, Pinot, or Druid.. Experience designing and operating infrastructure across multiple cloud regions, including workload isolation and cost-performance trade-offs.. How We Take Care of You:. Competitive Salary & Stock Options. Health Benefits. New Hire Home-Office Setup: One-time USD $500. Monthly Stipend: USD $150 per month via a Brex Card. Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.. Recruitment Privacy Policy. Create a Job Alert. Interested in building your career at Alpaca ? Get future opportunities sent straight to your email.. Create alert. Apply for this job. *. indicates a required field. Autofill my application. First Name. *. Last Name. *. Email. *. Phone. Country. *. Phone. *. Location (City). *. Locate me. Resume/CV. *. Attach. Attach. Dropbox. Google Drive. Enter manually. Enter manually. Accepted file types: pdf, doc, docx, txt, rtf. Cover Letter. Attach. Attach. Dropbox. Google Drive. Enter manually. Enter manually. Accepted file types: pdf, doc, docx, txt, rtf. LinkedIn Profile. *. Are you able to work during Eastern Time Zone/market hours?. *. Select.... Can you describe the data volume and latency requirements for the most challenging aspect of the data platform you developed?. *. Could you provide an example of open-source data stack components that facilitated the implementation you mentioned above . *. 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