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Data Engineer

  • Data Engineer job type Posted on: Nov 02, 2026
  • Data Engineer experience level Open Select
  • Data Engineer employment type New York, New York
  • Data Engineer salary Salary: $180,000 per year
  • Data Engineer employment type Onsite
  • Data Engineer salary Full-time

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Job Title :

Data Engineer

Job Type :

Full-Time

Job Location :

New York New York United States

Remote :

No

Jobcon Logo Job Description :

Data EngineerLocation: New York, NY (On-site)Comp: $180k - $200k + EquityIndustry: FinTech / AIWho you'll joinAn 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.What you'll doBuild and run production data pipelines with full operational ownership.Design schemas that model financial domains and absorb new data sources cleanly.Resolve entities and map identifiers across vendor feeds, APIs, and scraped sources.Onboard third-party data including messy vendor feeds, partner APIs, and PDFs.Monitor data quality using validation, contracts, freshness checks, and lineage tools.Model reference data covering security masters, corporate actions, and filings.Instrument pipelines for observability and act on failures without hand-holding.Who you areSpent several years running production pipelines with real orchestration ownership.Write strong SQL and Python without needing scaffolding or close review.Model data well and can explain why a schema is designed the way it is.Understand public markets reference data, corporate actions, and identifier standards.Communicate clearly and flag problems early without being chased.Work autonomously and take problems from discovery through to production.Bonus: familiar with streaming or tick data, time-series storage, or knowledge graphs.Tech stackPython, SQL, Airflow, Dagster, Prefect, data warehouse or lakehouse (e.g. Snowflake, BigQuery, Databricks), ISIN, CUSIP, SEDOL, FIGI, RIC, Bloomberg, LSEG / Refinitiv, S&P, FactSet, ICEWhy you'll thriveWork directly with the Head of Data on a small team where your choices matter.Own your work end to end, from ingestion through to production monitoring.Public markets data is the core of the product, not a side concern.Join at a stage where the data architecture is still being defined and built.Work on-site in New York with a team that holds a high technical bar.

Jobcon Logo Position Details

Posted:

Nov 02, 2026

Reference Number:

10440_4484248299

Employment:

Full-time

Salary:

$180,000 per year

City:

New York

Job Origin:

APPCAST_CPC

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Data EngineerLocation: New York, NY (On-site)Comp: $180k - $200k + EquityIndustry: FinTech / AIWho you'll joinAn 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.What you'll doBuild and run production data pipelines with full operational ownership.Design schemas that model financial domains and absorb new data sources cleanly.Resolve entities and map identifiers across vendor feeds, APIs, and scraped sources.Onboard third-party data including messy vendor feeds, partner APIs, and PDFs.Monitor data quality using validation, contracts, freshness checks, and lineage tools.Model reference data covering security masters, corporate actions, and filings.Instrument pipelines for observability and act on failures without hand-holding.Who you areSpent several years running production pipelines with real orchestration ownership.Write strong SQL and Python without needing scaffolding or close review.Model data well and can explain why a schema is designed the way it is.Understand public markets reference data, corporate actions, and identifier standards.Communicate clearly and flag problems early without being chased.Work autonomously and take problems from discovery through to production.Bonus: familiar with streaming or tick data, time-series storage, or knowledge graphs.Tech stackPython, SQL, Airflow, Dagster, Prefect, data warehouse or lakehouse (e.g. Snowflake, BigQuery, Databricks), ISIN, CUSIP, SEDOL, FIGI, RIC, Bloomberg, LSEG / Refinitiv, S&P, FactSet, ICEWhy you'll thriveWork directly with the Head of Data on a small team where your choices matter.Own your work end to end, from ingestion through to production monitoring.Public markets data is the core of the product, not a side concern.Join at a stage where the data architecture is still being defined and built.Work on-site in New York with a team that holds a high technical bar.

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