{"schemaVersion":"jobsearcher.job.v1","id":"d6834e4f7ef738d2f6285ce9","url":"https://jobsearcher.com/jobs/d6834e4f7ef738d2f6285ce9","canonicalUrl":"https://jobsearcher.com/jobs/d6834e4f7ef738d2f6285ce9","title":"Data Architect Data Analytics","description":"Data Engineer Location: New York, NY (On-site)\rComp: $180k - $200k + Equity \rIndustry: FinTech / AI \r\rWho you'll join \r\rAn early-stage fintech building a production-grade data platform for public markets. The data team is small, works close to the product, and takes full ownership of what it ships. If you have spent time at a buy-side data firm, you will recognize the standard they are aiming for. \r\rWhat you'll do \r\rBuild and run production data pipelines with full operational ownership. \rDesign schemas that model financial domains and absorb new data sources cleanly. \rResolve entities and map identifiers across vendor feeds, APIs, and scraped sources. \rOnboard third-party data including messy vendor feeds, partner APIs, and PDFs. \rMonitor data quality using validation, contracts, freshness checks, and lineage tools. \rModel reference data covering security masters, corporate actions, and filings. \rInstrument pipelines for observability and act on failures without hand-holding. \r\rWho you are \r\rSpent several years running production pipelines with real orchestration ownership. \rWrite strong SQL and Python without needing scaffolding or close review. \rModel data well and can explain why a schema is designed the way it is. \rUnderstand public markets reference data, corporate actions, and identifier standards. \rCommunicate clearly and flag problems early without being chased. \rWork autonomously and take problems from discovery through to production. \rBonus: familiar with streaming or tick data, time-series storage, or knowledge graphs. \r\rTech stack \r\rPython, SQL, Airflow, Dagster, Prefect, data warehouse or lakehouse (e.g. Snowflake, BigQuery, Databricks), ISIN, CUSIP, SEDOL, FIGI, RIC, Bloomberg, LSEG / Refinitiv, S&P, FactSet, ICE \r\rWhy you'll thrive \r\rWork directly with the Head of Data on a small team where your choices matter. \rOwn your work end to end, from ingestion through to production monitoring. \rPublic markets data is the core of the product, not a side concern. \rJoin at a stage where the data architecture is still being defined and built. \rWork on-site in New York with a team that holds a high technical bar.","company":"Open Select","rawCompany":"open select","city":"Glens Falls","state":"NY","isRemote":false,"isActive":false,"createdAt":"2026-11-01T11:23:16.678Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Architect Data Analytics","description":"Data Engineer Location: New York, NY (On-site)\rComp: $180k - $200k + Equity \rIndustry: FinTech / AI \r\rWho you'll join \r\rAn early-stage fintech building a production-grade data platform for public markets. The data team is small, works close to the product, and takes full ownership of what it ships. If you have spent time at a buy-side data firm, you will recognize the standard they are aiming for. \r\rWhat you'll do \r\rBuild and run production data pipelines with full operational ownership. \rDesign schemas that model financial domains and absorb new data sources cleanly. \rResolve entities and map identifiers across vendor feeds, APIs, and scraped sources. \rOnboard third-party data including messy vendor feeds, partner APIs, and PDFs. \rMonitor data quality using validation, contracts, freshness checks, and lineage tools. \rModel reference data covering security masters, corporate actions, and filings. \rInstrument pipelines for observability and act on failures without hand-holding. \r\rWho you are \r\rSpent several years running production pipelines with real orchestration ownership. \rWrite strong SQL and Python without needing scaffolding or close review. \rModel data well and can explain why a schema is designed the way it is. \rUnderstand public markets reference data, corporate actions, and identifier standards. \rCommunicate clearly and flag problems early without being chased. \rWork autonomously and take problems from discovery through to production. \rBonus: familiar with streaming or tick data, time-series storage, or knowledge graphs. \r\rTech stack \r\rPython, SQL, Airflow, Dagster, Prefect, data warehouse or lakehouse (e.g. Snowflake, BigQuery, Databricks), ISIN, CUSIP, SEDOL, FIGI, RIC, Bloomberg, LSEG / Refinitiv, S&P, FactSet, ICE \r\rWhy you'll thrive \r\rWork directly with the Head of Data on a small team where your choices matter. \rOwn your work end to end, from ingestion through to production monitoring. \rPublic markets data is the core of the product, not a side concern. \rJoin at a stage where the data architecture is still being defined and built. \rWork on-site in New York with a team that holds a high technical bar.","datePosted":"2026-11-01T11:23:16.678Z","dateModified":"2026-11-01T11:23:16.678Z","hiringOrganization":{"@type":"Organization","name":"Open Select","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Glens Falls","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d6834e4f7ef738d2f6285ce9"},"url":"https://jobsearcher.com/jobs/d6834e4f7ef738d2f6285ce9"}}