Data Engineer

Overview

£40,000 - £60,000 Base + Performance Related Bonus + Benefits

TL;

DR

• Location: UK‑based, fast growing data and AI consultancy specialising in the energy sector
• Cloud: Strong AWS, Azure or GCP (multi‑cloud desirable, certs a plus)
• Consultancy / Energy
  
  Experience:
  
  Highly beneficial, not essential
• Visa Sponsorship: Not available – you must already have the right to work in the UK
• Flexibility: We welcome part‑time, condensed hours, job‑shares and other arrangements – if you’re unsure, apply and let’s talk
• Diversity & Inclusion: We want a broad mix of people and perspectives

Who We Are

Hypercube Consulting is a rapidly scaling data‑and‑AI specialist focused on the energy sector. We pair deep domain know‑how with modern technology to help utilities, renewables and low‑carbon innovators unlock value from data. Learn more about how we think on our founder’s blog at the URL:

As a data engineer, you will truly understand a client’s requirements to build, test and deploy data solutions that help customers deliver more value from their data. You'll get stuck into the end‑to‑end data workflow - everything from realtime event streaming to big data analytics using modern tools across a range of technology stacks - with the opportunity to develop production‑grade solutions using the most current technology.

• Requirements Gathering - Understand and translate end-user requirements into designs and delivery plans for effective data solutions
• Data Platforms & Pipelines - Develop, test, deploy, and maintain highly automated data platforms, pipelines and applications using modern cloud technologies
• Data Quality - Analyse and resolve data quality issues
• Communicate - Effectively produce high‑quality communications, documentation, and presentations of solutions for colleagues
• Commercial, Pre‑Sales & Outreach - Working with the business development team to shape and win new projects. Contribution to Hypercube’s blog and other outreach efforts

We understand that this list is extensive – please apply if you fit some or only part of it. We want to see the broadest range of possible candidates from a diverse mix of backgrounds. Technical skills are only part of the equation.

Ideally, you will have hands‑on experience with the following in a previous role:

• Python
• SQL
• Data Lakes/Lake houses and analytical tools (Databricks, Azure Fabric/One Lake, AWS Lake Formation, Spark, Athena, etc.)
• CI/CD and other Dev Ops practices such as IaC
• Testing

Additional experience with the following would be beneficial but not essential:

• Data Warehousing (Snowflake, Redshift, Synapse, Big Query, etc.)
• Relational, No
  
  SQL, graph and vector databases
• Containers and related services (Docker, Kubernetes, container Registries, etc)
• Orchestration tools - Apache Airflow, Prefect or cloud‑native tools
• Backend software development (Java, APIs, Scalability, Logging and Monitoring etc.)
• MLFlow and other MLOps / Machine Learning Engineering processes to support advanced analytical use cases
• LLMs and Agentic AI
• BI tools such as Tableau / Power BI

Other desirable skills and experience

• Building projects or sharing knowledge in public – whether that be contributing to open source, blogging, You Tube, content creation, speaking at events, or similar.
• Experience translating designs of data solutions into action
• Analysis/requirements gathering, solution design, and implementation of data platform and cloud technologies
• Experience in collaborating in multi‑disciplinary teams, including software engineers, Dev Ops and infrastructure teams, AI/ML engineers, data scientists etc.
• Experience in implementing integrations of data platforms to various types of external and on‑premises systems
• Exceptional communication skills, both written and verbal – able to translate complex technical subject matter into easily understood presentations and written documentation for mixed technical audiences.

• High Impact: Solve difficult problems for leading energy players tackling net‑zero challenges
• Flexible Working: Remote/hybrid, part‑time or condensed options – we measure outcomes, not chair‑time
• Personal Brand: We sponsor conferences,…