Overview We are seeking a capable intermediate‑level Data Engineer with strong MLOps and analytics experience to support the design, optimisation, governance, and monitoring of enterprise data and machine learning pipelines within a Databricks ecosystem. Successful candidates will play a critical role in ensuring scalable, sustainable, and efficient data processes while supporting analytics, ML model deployment, integrations, and reporting initiatives. This position offers strong long‑term potential with multi‑year engagement opportunities. Key Responsibilities Design, optimise and maintain scalable data pipelines within Databricks. Ensure pipelines are efficient, sustainable, user‑friendly, and easy to debug. Implement and maintain Delta Tables and Databricks notebooks. Perform data validation and basic data quality checks. Monitor and improve process governance and operational efficiency. Train, deploy and monitor machine learning models using MLflow. Analyse model performance and business impact. Support model lifecycle management and deployment best practices. Develop Power BI dashboards and business insight reporting. Support data‑driven decision‑making through analytics solutions. Monitor API data integrations and data sends. Troubleshoot integration failures and ensure data consistency. Manage Git‑based workflows including pull requests, branch synchronisation and merge conflict resolution. Collaborate with cross‑functional teams including data scientists, analysts and business stakeholders. Qualifications Degree or Diploma in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics or a related field. 3–5 years’ experience in Data Engineering or related roles. Hands‑on experience with Databricks, Delta Tables, MLflow, Power BI and Python/SQL. Strong experience with Git version control workflows. Exposure to API integrations and monitoring. Technical Skills Databricks Delta Tables Databricks Notebooks MLflow Python SQL Power BI Git / Azure DevOps API Monitoring & Integration Data Pipeline Optimisation Data Quality & Governance Advantageous Skills Azure Data Services CI/CD for ML pipelines Spark / PySpark Cloud‑based data platforms MLOps best practices Soft Skills Strong analytical and problem‑solving abilities Attention to detail Strong communication skills Ability to work in collaborative environments Self‑driven and proactive mindset #J-18808-Ljbffr