Machine Learning Data Engineer
selby jenningsBethesda (MD)
About the role
We are hiring a hands‑on Machine Learning Data Engineer for a boutique asset management company to design, build, and scale a production‑grade, Snowflake‑centric data platform that powers analytics and machine‑learning use cases across the firm.
This is a builder role. You will own data pipelines end‑to‑end and work closely with technology, analytics, and business stakeholders to deliver reliable, well‑governed, ML‑ready datasets.
Key Responsibilities:
Design, build, and operate scalable data pipelines ingesting data from internal systems, APIs, and external providers
Own and evolve a Snowflake‑based warehouse / lakehouse, including schema design, transformations, and optimisation
Implement ELT processes to create trusted datasets for analytics and machine learning
Build and maintain ML‑ready datasets and feature pipelines supporting experimentation and production models
Support batch and near‑real‑time data workflows
Ensure data quality, freshness, and reliability through monitoring, validation, and alerting
Apply best practices around data governance, access control, and documentation
Partner with analytics and business teams to translate requirements into durable data products
Continuously improve performance, scalability, and cost efficiencyRequired Experience 5+ years’ experience in data engineering or ML‑data engineering roles
Strong, hands‑on Snowflake experience (production usage, not exposure)
Advanced Python and SQL
Experience with data modelling for analytics and ML use cases
Familiarity with orchestration tools (e.g. Airflow, Dagster)
Experience working in production, high‑accountability environments
Strong communicator, comfortable working cross‑functionallyHighly PreferredExposure to Databricks / Spark
Background in financial services or regulated data
Experience in lean, execution‑focused teamsThis Role Is Not A pure Data Scientist or ML research role
A BI‑only or reporting‑focused data role
A DevOps / cloud infrastructure role
Before you apply
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A number in mind
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Your notice period
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