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Flow Traders

Core Data Engineer

Amsterdam

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hirly's read of this role

Role family
Data & ML
Seniority
Mid level
Country
NL
Work mode
On-site / unstated
First seen by hirly
23 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Flow Traders is looking for a Core Data Engineer to own the end-to-end lifecycle of our most fundamental data products, including our Security Master; our reconciled ETF Compositions; high-resolution historical market data; and records of our trades, orders, quotes, and inquiries. High-quality data is the cornerstone of Flow Traders' strategic direction - beyond reducing complexity and BAU for stakeholders across the organization, quality data is a key requirement for our growth of quantitative trading styles. ​

Specifically, you will craft and execute the blueprint for these products, leveraging our Data Platform to build and monitor automated pipelines which ensure that users across the organization have reliable data at their fingertips when they need it. Further, you will become an expert in these data sets, leveraging that knowledge to optimize our use of the data we have and explore new sources for additional value. Finally, you will constantly collaborate with teams across the organization to ensure that our in-house systems are designed with data in mind, streamline additional data-related workflows, and work with stakeholders to maximize the value they extract from our data. ​

As the architect and guardian of our most valuable data, you will have a unique opportunity to make your mark on Flow Traders. You will be accountable for delivering these data products at an exceptional level of quality, ensuring that they are not only timely and pristine, but powerful enough to drive Flow Traders' future growth. Ultimately, your work will not only provide highly visible benefits that every division feels every day, but it will also deliver one of the most important building blocks to the firm's strategic growth for the years to come. ​

What you will do

Craft datasets with quants. Take an underspecified research question and turn it into the right dataset: aligned, adjusted, point-in-time correct, documented, and reproducible. ​

Develop and own the end-to-end lifecycle of these data products. Build and maintain pipelines, develop quality checks, correct day-to-day operational issues, and systematize/automate manual processing steps ​

Own data quality where it matters. Design the checks and alerts that catch the problems that would actually hurt a strategy, and deliberately leave out the ones that are just noise. ​

Build shared foundations. Reference data, instrument identifiers, corporate actions and vendor feeds that every researcher and trading desk depends on. ​

Keep critical pipelines running. Markets in several regions, and digital asset markets that never close, depend on this data. You will be part of a team that supports it across time zones. ​

What you need to succeed

Required ​

Analytics or data engineering experience, ideally at a startup or scale-up through a growth phase ​

Strong data modelling and data quality practice: tests, contracts, lineage, observability in production ​

Strong proficiency in Python (ideally familiarity with another statically-typed language) ​

Working proficiency with SQL and relational databases, and version control systems ​

Demonstrated ability to work with large datasets and familiarity with big data solutions ​

You have owned something in production, not only built it ​

You enjoy working directly with the people who use your 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 ​

Strongly preferred ​

Experience with financial data: prices, market data, transactions, 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 (esp. GKE, Dataproc , and Big Query), strongly preferred ​

Experience with Polars, Pandas, Spark, Apache Beam, Apache NiFi ​

Experience at a trading firm, systematic fund, brokerage, crypto exchange or market data company ​

On-call or incident response experience

  • What we offer
  • At Flow Traders, we create the conditions for hard‑working, high‑performing people to do their best work. From a thorough onboarding and ongoing access to Flow Academy, to latest technology and a collaborative, non‑hierarchical culture, we give you the tools, ownership, and support to move fast and drive outcomes. We keep a close‑knit, small‑company feel while offering competitive salary, annual discretionary profit share, and comprehensive benefits, so talent can grow here, and stay here. See our benefits below:

Flow Academy and opportunities to attend domain-related conferences

Daily catered lunch, great coffee, and a fully stocked kitchen and snack bar

In-house Bar and Lounge with arcade, table tennis, billiards, and game consoles

Company boat

In-house gym and sessions with our nutritionist or personal trainer

Bi-weekly massages

Annual company trip and a variety of events throughout the year, such as the New Years Event

Global rotations across our offices worldwide

and more

Flow Traders does not accept unsolicited resumes from any professional staffing or search firms. All resumes, and any other information identifying potential candidates, submitted to any employee at Flow Traders via-email, the Internet or directly without a valid and signed search agreement will be deemed free to contact by Flow Traders without any restrictions and no placement fee of any kind will be paid in the event the candidate is hired by Flow Traders.

Original posting on Flow Traders's site ↗

Listed on hirly, a job board. hirly is not the employer: Flow Traders is hiring for this role.

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