Own the end-to-end build of reliable data pipelines, performant storage, and operational AI.In this role, you will blend data engineering with applied ML to power analytics, automation, and decisioning.Client DetailsA transformation focused organisation where data and AI drive measurable impact. Collaborative, fast, and big on continuous improvement, with ethics and governance baked in.Description* Pipeline & platforms: Build/operate scalable ETL/ELT and streaming workflows. * Data foundations: Optimise storage, query performance, and model-serving layers. * Applied AI: Deploy and maintain ML/LLM workloads tied to clear business use-cases. * Partner well: Shape high-quality datasets with analysts/scientists; ship usable outputs. * Operate safely: Implement MLOps, data/model governance, security, and compliance. * Improve continuously: Instrument, monitor, and iterate for cost/perf/reliability.Job Offer* Impact at scale in a dedicated data function, shaping data & AI strategy. * Modern tooling, cross-functional squads, and meaningful problems to solve.
* Bachelor's in Computer Science, Data Science, Engineering, or similar. * Must have 5 years in data engineering; with at least 2 years applied AI/ML in production. * Strong ETL/ELT, data architecture, and Azure (e.g., ADF, Databricks, Synapse). * Proficient in Python, SQL and common ML frameworks (e.g., TensorFlow, PyTorch). * Working knowledge of data & model governance and responsible/ethical AI. * Clear communicator who can align stakeholders and land outcomes.
