Core Data Engineer

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 su