Core Data Engineer

Flow Traders • New York, NY

2h • $165,000 - $210,000

About The Position

Flow Traders is seeking a Core Data Engineer to own the end-to-end lifecycle of fundamental data products, including the Security Master, reconciled ETF compositions, high-resolution historical market data, and records of trades, orders, quotes, and inquiries. The role is central to the firm’s focus on reducing complexity and operational work while providing high-quality data to support quantitative trading and strategic growth.

The engineer will design and execute the blueprint for these data products, using Flow Traders’ Data Platform to build and monitor automated pipelines. They will develop deep expertise in the underlying datasets, improve how existing data is used, and explore new data sources. The role also involves collaborating across the organization to ensure in-house systems account for data needs, streamline data workflows, and help stakeholders get more value from data.

The position is accountable for delivering timely, reliable, high-quality data products that support researchers, trading desks, and other divisions. It includes supporting critical pipelines across multiple market regions and digital asset markets that operate continuously, as part of a team working across time zones.

Requirements

• Analytics or data engineering experience, ideally at a startup or scale-up during a growth phase.
• Strong data-modelling and data-quality practices, including tests, contracts, lineage, and production observability.
• Strong proficiency in Python; familiarity with another statically typed language is ideal.
• Working proficiency with SQL, relational databases, and version control systems.
• Demonstrated ability to work with large datasets and familiarity with big data solutions.
• Experience owning something in production, rather than only building it.
• Enjoyment of working directly with the people who use the data.
• Strong interpersonal and communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
• Ability to balance individual stakeholder requirements with data quality, consistency, and broad applicability.

Nice To Haves

• Experience with financial data, such as prices, market data, transactions, and instruments.
• Familiarity with point-in-time data, look-ahead bias, and survivorship bias.
• Experience with a modern cloud data stack, such as Spark or Databricks, dbt, a cloud warehouse, and orchestration.
• Experience with Airflow, Kafka, and GCP, especially GKE, Dataproc, and BigQuery.
• Experience with Polars, Pandas, Spark, Apache Beam, or Apache NiFi.
• Experience at a trading firm, systematic fund, brokerage, crypto exchange, or market data company.
• On-call or incident-response experience.

Responsibilities

• Work with quants to turn underspecified research questions into aligned, adjusted, point-in-time-correct, documented, and reproducible datasets.
• Develop and own the end-to-end lifecycle of data products, including building and maintaining pipelines, developing quality checks, resolving day-to-day operational issues, and automating manual processing.
• Design data-quality checks and alerts that identify problems likely to harm a strategy while avoiding noisy checks.
• Build shared data foundations, including reference data, instrument identifiers, corporate actions, and vendor feeds used by researchers and trading desks.
• Support critical data pipelines serving markets in multiple regions and digital asset markets that operate continuously, working as part of a team across time zones.
• Collaborate across the organization to ensure systems are designed with data in mind, streamline data-related workflows, and help stakeholders maximize the value of data.

Benefits

• All employees are eligible to share in the company’s success through annual discretionary variable remuneration based on company, group, and individual performance and contribution.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed