Digital Intelligence Lead

Siemens Energy
Lincoln
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Research Scientist: Data Science and Machine Learning

Teacher of Computer Science and Artificial Intelligence Lead

Senior Research Scientist: Data Science and Machine Learning AIP

Senior Research Scientist: Data Science and Machine Learning AIP

Senior Data Scientist

Senior Machine Learning Engineer

Digital Intelligence Lead

About the Role

LocationUnited Kingdom Lincolnshire Lincoln Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Industrial Turbomachinery Ltd. Organization Gas Services Business Unit Distributed Full / Part time Full-time Experience Level Experienced Professional

A snapshot of your day

As the Digital Intelligence Lead, you will be responsible for guiding the business on data architecture and data engineering to best deliver strategic data and business intelligence solutions.

You will also be responsible for developing application services to our internal customers, that are defined by our business processes. You will need to interface and network across all business functions within the OneSGT organisation and will have the opportunity to mentor and guide the existing Digital Intelligence (DI) team who operate out of the Lincoln site. In addition, you will provide real time strategic direction for the company's existing third parties working on data modelling projects via university links.

Key responsibilities

Mentor and support the progression of Digital Intelligence colleagues in the Transformation team with particular respect to Data Engineering and Data Architecture. Work multi-functionally with the Head of Transformation and the Digitalisation Manager in formulating a strategy for OneSGTs Digital and Data infrastructure and act as their main point of contact for Data Infrastructure for OneSGT. Deliver digital based solutions to improve the operation, efficiency, and accuracy of functions across the OneSGT business. Provide direction for, and assist in, the development of a digital architecture that will facilitate a multitude of different project usecases. Facilitate the implementation of a Data Governance process. Work alongside internal and external partners to translate their business requirements into workable solutions. Optimise and innovate our end to end data pipeline Identify and work with related projects to address any interdependencies, ensuring a coordinated portfolio of projects. Identify, share and promote best practices and lessons learned to create a culture of learning and good practice that supports continuous improvement.

What you bring

Relevant BSc or MSc degree or equivalent experience essential Significant experience with digital programmes and project working environments Experience using data science programming languages, such as SQL, Python, and R Proven understanding of industry standard processes for data governance and infrastructure Experience leading the planning and task management of Data Engineering/Science projects Demonstrable experience leading teams to deliver positive outcomes to time, budget and quality, and coaching and mentoring other colleagues Ability to create statements of work/ project charters and manage projects in our Project Management software (OnePM) Knowledge and understanding of common applications SAP, Team Centre, Salesforce, SharePoint, Power Platform desirable Experience of working with databases ( the snowflake data platform), managing Data Migration and Integration projects, and using Data visualisation software, such as Tableau or PowerBI advantageous

Who is Siemens Energy?

At Siemens Energy, we are more than just an energy technology company. We meet the growing energy demand across 90+ countries while ensuring our climate is protected. With more than 92,000 dedicated employees, we not only generate electricity for over 16% of the global community, but we’re also using our technology to help protect people and the environment.

Our distributed team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decolonisation, new technologies, and energy transformation.

Our Commitment to Diversity

Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion and our combined creative energy is fuelled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energise society, all of society, and we do not discriminate based on our differences.

Rewards/Benefits

We offer options to work flexibly, especially after successful onboarding – whether it be working remotely, flexible working hours or a combination of both Working with a global team Opportunities to work on and lead a variety of innovative projects Encouraging work culture Employer sponsored pension plans and stock plans Many advantages of a collective agreement We value equal opportunities and encourage applications from people with disabilities


#LI-PS1

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.