Data engineer in financial markets

Flow Traders; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Competitive salary

Profit sharing

Flow Academy

Daily catered lunch

Fully stocked kitchen & snack bar

In-house gym & wellness programs

Company boat

Annual company trip

Global office rotations

Job summary

Flow Traders in Amsterdam is seeking a Core Data Engineer to own the end-to-end lifecycle of our fundamental data products, including Security Master, reconciled ETF compositions, high-resolution market data, and trade records. You will build and operate data pipelines across multiple regions, ensuring accuracy and timeliness for traders and researchers.

The role requires strong Python and SQL skills, data modeling, and experience with big data stacks.

Qualifications

• Analytical or data engineering background, startup/scale-up experience.
• Strong data modeling and data quality practices.
• Proficient in Python; SQL and databases; version control.
• Experience with large datasets and production ownership.
• Excellent collaboration with stakeholders.

Responsibilities

• Own end-to-end lifecycle of data products and datasets.
• Build and maintain pipelines with quality checks and alerts.
• Develop datasets with researchers; manage reference data and identifiers.
• Keep critical pipelines running across regions and markets.
• Collaborate with quants, traders and data stewards across time zones.

Skills

Python

SQL

Data modeling

Data quality

Big data

Observability

Tools

Airflow

Kafka

GCP

Spark/Databricks

dbt

Job description

Описание:

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.

Задачи:

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.

Требования:

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 Будет плюсом: 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

Условия:

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. 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