We're looking for a highly autonomous Senior Data & ML Engineer who wants to be the true owner of how data works for the teams they support, delivering solutions completely end-to-end, from initial scoping and design through to delivery, implementation, and full business adoption.
What you'll be doing:
•Design, build, and maintain data pipelines and transformations on Databricks using Python, PySpark, and SQL.
•Deploy, operationalize, and monitor machine learning models (MLOps) in production environments.
•Build and maintain data marts as the primary source of truth for key business domains.
•Apply data modelling practices (e.g., dimensional modelling, medallion architecture) to maintain data consistency and reusability.
•Act as the primary data partner for specific business areas, understanding their processes, goals, and pain points.
•Deliver end-to-end solutions, managing scoping, discovery, design, delivery, user adoption, and iteration.
•Gather and translate business requirements into technical solutions.
What you'll need to be successful:
•5+ years of experience as a Data/ML Engineer, with a track record of independently owning data/ML solutions from scoping to adoption.
•Proficiency in Python, SQL, and PySpark/Spark.
•Experience with modern data platforms, such as Databricks (Delta Lake, Unity Catalog, MLflow, workflows).
•Stakeholder management skills, with the ability to navigate commercial and engineering discussions, manage expectations, and drive cross-functional decisions.
•Data modelling skills and experience designing data marts for analytics and reporting.
•Experience building production pipelines with orchestration, testing, monitoring, and version control.
•Experience with BI tools (e.g., Preset, Tableau, Metabase, Power BI) and data usability principles.
•Demonstrated accountability for project outcomes and commercial impact.
