Machine Learning Data Engineer

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