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.
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
At Flow Traders, we acknowledge the importance of open and transparent communication whether it be with our employees, our stakeholders, or our local and global communities. When it comes to salary, Flow Traders uses reliable market research to create base ranges. Where candidates will fall within the range depends on a few different factors including but not limited to level of experience, location, and specific skill set. We also consider ourselves one global team, and to demonstrate that, all employees are eligible to share in the company’s success through an annual discretionary variable remuneration allocated based on company, group and individual performance and contribution.
Per NYC salary transparency law, the total compensation for this role includes a base range of $165,000 to $210,000 plus annual discretionary variable remuneration.
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.
#LI-MM1Skills Required
- Analytics or data engineering experience, ideally in a startup or scale-up through a growth phase
- Strong data modeling and data quality practices, including tests, contracts, lineage, and production observability
- Strong proficiency in Python
- Familiarity with another statically typed language
- Working proficiency with SQL and relational databases
- Working proficiency with version control systems
- Experience working with large datasets and familiarity with big data solutions
- Experience owning systems or products in production
- Ability to work directly with data users
- Strong interpersonal and communication skills
- Ability to collaborate with technical and non-technical stakeholders
- Ability to balance stakeholder requirements with data quality, consistency, and broad applicability
- Experience with financial data such as prices, market data, transactions, or instruments
- Familiarity with point-in-time data, look-ahead bias, and survivorship bias
- Experience with a modern cloud data stack, including 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
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What We Do
Since 2004, Flow Traders has been a principal trading firm and one of the world’s largest liquidity providers, specialised in Exchange Traded Products (ETPs). Our headquarters in Amsterdam and offices in New York, Singapore, Hong Kong, Milan and Cluj accommodate more than 500 employees. Throughout the years, Flow Traders has received the industry’s recognition, winning numerous awards and has been listed as a company since 2015. Our non-hierarchical approach stimulates innovation and development. We value creative minds and out-of-the-box thinkers and challenge them to make full use of their capacities. Our demanding, high-paced environment continuously puts us to the test. Flow Traders fosters a strong team-oriented culture which rewards people for their contributions to the company as a whole rather than only in their direct area of responsibility. At Flow Traders, we focus on professional and personal development; we encourage our people to be the best at anything they do by offering the right training. On top of that, we have our private gym where our health coaches provide our people with the right personal sports programs. We invest in our hard working people, because they hold the key to our success.
