Core Data Engineer
Flow Traders · On-site · Full-time · New York
Posted (1h ago)
- Employer posted
- First seen here
- Repost check
- Same job ID since we first saw it on Oct 22, 2026. If Flow Traders reposts it, we keep the original posting date.
- Pay
- $165k–$210k a year (from the description)
- Level
- Mid-level
- Work setup
- On-site
- Tech mentioned
- Spark, Python, SQL, dbt, Airflow, Kafka, GCP
- Flow Traders hiring
- 2 roles posted in the last 30 days
Job description
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
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.
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Flow Traders job ID: 1719
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