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Data Engineer (Automation)Network IT • Milton Keynes, England, United Kingdom
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Data Engineer (Automation)

Network IT
  • GB
    Milton Keynes, England, United Kingdom
  • GB
    Milton Keynes, England, United Kingdom
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À propos

Role: Data Engineer (Automation) Location: Milton Keynes (Hybrid – 3 Days In-Office Weekly) Salary: £45,000 - £55,000 Network IT are supporting a large, enterprise-scale organisation as they continue to evolve and modernise their Data Analytics and Automation Platform; we’re looking for an experienced Data Engineer to design, build, and optimise secure, automated data pipelines that enable scalable analytics, business intelligence, and data‑driven decision‑making across multiple business units. This is a highly technical role with strong exposure to cloud and on‑prem data platforms, automation, and emerging AI‑driven capabilities, and is specifically suited to candidates with strong, hands‑on data engineering experience, particularly in building, operating, and optimising complex data pipelines, data models, and integration workflows at scale. Role Overview and Responsibilities As a Data & Automation Engineer, you will be responsible for the end‑to‑end delivery, operation, and continuous improvement of enterprise data pipelines and analytics platforms. You’ll work closely with architects, application managers, and international teams to ensure data solutions are reliable, scalable, and aligned with data governance standards. Key responsibilities include: Designing, developing, and maintaining automated end‑to‑end data pipelines across cloud and on‑premise source systems. Delivering reliable data ingestion, transformation, and delivery processes using technologies such as Azure Data Factory, Databricks, SSIS, and SQL. Reducing manual interventions through automation and standardisation, including data preparation, feature engineering, and training‑data pipelines. Preparing data models and datasets (DWH / Lakehouse) to support business intelligence, analytics, and operational reporting. Monitoring and supporting live data pipelines, resolving issues in line with ITIL best practices, and implementing proactive alerting and self‑healing mechanisms. Identifying and implementing performance optimisations across data pipelines, queries, and reporting workloads. Supporting data governance processes, including data archiving, masking, encryption, and versioning, with opportunities to integrate AI‑driven automation. Contributing to CI/CD processes for data pipelines, ensuring releases are tested, compliant, and deployed with minimal operational impact. Collaborating with cross‑functional and international teams to support aligned, scalable data operations. Supporting the ongoing evolution and execution of the organisation’s data strategy.Essential Skills and Experience To be successful in this role, you will bring: Strong commercial experience delivering end‑to‑end data engineering and automation solutions in complex environments. Advanced SQL skills, including performance tuning and optimisation across large datasets. Knowledge of Python or R for data processing or analytics. Hands‑on experience with data integration and ingestion tools such as Azure Data Factory and Databricks. Proven experience in data modelling, data warehousing, and relational database platforms (e.g. MS SQL Server). Experience designing cloud‑native and/or on‑prem data solutions. Exposure to automation and AI‑enabled data processes, with awareness of LLM use cases within data workflows. Experience working in Agile delivery environments (Scrum, Kanban, DevOps). Strong analytical and problem‑solving skills, with the ability to translate complex data into meaningful insights. Excellent communication skills and the ability to work effectively with both technical and non‑technical stakeholders.Desirable Experience Experience coordinating or supporting AI / ML initiatives within data platforms. Experience working within large, regulated, or international organisations
  • Milton Keynes, England, United Kingdom

Compétences linguistiques

  • English
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