Middle Data Engineer

<h3><strong>Responsibilities:</strong></h3> <ul> <li>Build, maintain, and optimise scalable ETL/ELT pipelines (batch and near-real-time) on Azure Data Cloud Platform (e.g., Data Lake, Microsoft Fabric, Azure Data Factory).</li> <li>Develop and refine data models to support BI reporting, analytics, and ML/AI use cases.</li> <li>Write efficient, well-documented T-SQL and PySpark code following team coding standards.</li> <li>Implement automated testing, data validation, and monitoring (SLAs, alerts) to ensure pipeline reliability.</li> <li>Contribute to data governance practices, including lineage tracking, metadata management, and quality controls.</li> <li>Support CI/CD pipelines for data assets, ensuring version control and reproducibility.</li> <li>Partner with analytics engineers to scope, refine, and prioritise data requirements from business stakeholders.</li> <li>Work with Analysts, BI Developers, Data Scientists, and business teams to translate requirements into production-ready data solutions.</li> <li>Provide input on data readiness for machine learning and analytics projects.</li> <li>Contribute to the evolution of the ED&amp;I data platform, including tooling, standards, and documentation.</li> <li>Stay current with emerging data engineering patterns and technologies; propose improvements to team processes.</li> <li>Leverage AI-driven development tools (e.g., generative-AI code assistants, automated data profiling) to accelerate delivery.</li> <li>Support performance tuning and cost optimisation across the data platform.</li> </ul> <h3>Requirements:</h3> <ul> <li>3+ years in data engineering or a closely related role.</li> <li>Bachelor’s degree in Computer Science, Data Engineering, or a related field.</li> <li>Strong T-SQL skills and working proficiency in PySpark or Python for data processing.</li> <li>Hands-on experience with MS Azure Storage Explorer and SSMS.</li> <li>Hands-on experience with cloud-based data engineering services and orchestration tools (e.g., Azure Data Factory, Microsoft Fabric).</li> <li>Practical experience building ETL/ELT pipelines and dimensional or analytical data models.</li> <li>Familiarity with CI/CD practices in data engineering, including version control (Git) and automated testing.</li> </ul> <p><strong>Nice to have:</strong></p> <ul> <li>Experience with real-time or streaming data architectures.</li> <li>Experience with PowerShell, Apache Kafka, and/or KQL.</li> <li>Exposure to AI/ML workflows (feature engineering, data preparation for model training).</li> <li>Familiarity with Power BI or other BI/visualisation tools.</li> <li>&nbsp;Experience using AI productivity tools (e.g., ChatGPT, Claude, Copilot, Cursor) in day-to-day and data engineering tasks.</li> <li>Understanding of data security, privacy, and compliance considerations.</li> </ul><div class="content-conclusion"><p><strong>We offer*:</strong></p> <ul> <li>Flexible working format - remote, office-based or flexible</li> <li>A competitive salary and good compensation package</li> <li>Personalized career growth</li> <li>Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)</li> <li>Active tech communities with regular knowledge sharing</li> <li>Education reimbursement</li> <li>Memorable anniversary presents</li> <li>Corporate events and team buildings</li> <li>Other location-specific benefits</li> </ul> <p>*not applicable for freelancers</p></div>