Senior Data Engineer

Base Location: You'll be expected to spend 50% of your working week in one of the following locations Reading, Aberdeen, Perth or Glasgow

Salary: Salary: £ 42,600 - £64,000+ Performance-related bonus and a range of benefits to support your finances, wellbeing and family.

Working Pattern: Permanent | Full Time | Flexible First options available

The role

This is an exciting opportunity for a passionate and driven individual to make a meaningful impact within SSE Renewables. The successful candidate will bring a strong commitment to continuous improvement, adaptability, and a hands‑on approach to problem‑solving. A genuine enthusiasm for delivering high‑quality outcomes, combined with deep expertise in data management, is essential. If you thrive in a collaborative, forward‑thinking environment and are motivated by making a difference, we encourage you to apply.

The Renewables Digital IM and Data Team is scaling up the development of a governed, cost‑efficient data platform designed to deliver robust, actionable insights that support strategic decision‑making and drive measurable business value across the organisation.

As a Senior Data Engineer, you will design, build, and optimise data ingestion, transformation, and serving layers across OneLake, Lakehouse, Warehouse, and Synapse SQL/Spark—enabling reliable analytics, BI, and data science use cases across the Renewables business. You will collaborate with data architects, analysts, and product teams to deliver high‑quality ELT/ETL pipelines, model data for performance and usability, and apply best practices in security, data quality, and observability.

In this role, you will act as a technical lead within the Data & AI team, contributing to project scoping, providing expert guidance, and ensuring solutions are well‑architected and aligned with business needs. You will also mentor and support junior team members, helping them develop their skills and deliver strong engineering outcomes.

You Will

• Provide technical leadership, acting as an advisor during project scoping and offering internal consultancy to ensure solutions are well‑designed and aligned to business goals.
• Deliver Data Platform Engineering by building and maintaining metadata‑driven data pipelines using Fabric and Synapse, and developing Lakehouse/Warehouse layers using bronze/silver/gold patterns.
• Perform large‑scale transformations using Fabric Notebooks (PySpark/SQL) and Synapse Spark, and design performant data models integrated with Power BI and Direct Lake.
• Lead Governance, Security & Compliance practices, including implementing Purview lineage and cataloguing, enforcing RBAC and data masking, managing SLAs/SLOs, and supporting data standards across the platform.
• Drive DevOps, automation, and collaboration, working closely with analysts, BI developers, and product teams to refine requirements, deliver scalable solutions, and guide junior engineers.
• Shape the future direction of the data platform by contributing to technology evaluations and architectural decisions, including assessing emerging tools, cloud capabilities, and opportunities to evolve beyond the current Fabric/Synapse landscape where beneficial.

You Have

• A strong track record of delivering high‑quality data solutions in a complex, fast‑growing organisation, with the ability to balance priorities and collaborate effectively across technical and business teams.
• Excellent communication skills, enabling you to explain technical concepts clearly and work confidently with colleagues across the IM Apps & Data team and wider Renewables business.
• Deep expertise in modern Data Platform Engineering, with hands‑on experience building metadata‑driven pipelines using Microsoft Fabric and Synapse, developing Lakehouse/Warehouse architectures, and applying PySpark/SQL for large‑scale data processing and data quality management.
• Proven ability to design performant, user‑focused data models that integrate seamlessly with Power BI (including Direct Lake), along with a positive, solution‑driven approach to resolving challenges.
• Experience working with modern cloud and analytics ecosystems such as AWS or Databricks, bringing additional perspective and flexibility that complements our current Microsoft‑centric platform and supports future evolution of the data landscape.