National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Settlement analyst- Energy Sector

Vallum Associates
London
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Engineer

Job Title: Data Engineer (Data Flows)/Settlement analyst

Location: London- 2days/week

Duration: Permanent


Energy Sector Client Experience Required


Job Description

We are seeking a Data Engineer with a strong emphasis on energy industry expertise to join our dynamic team. This role is ideal for candidates who possess deep knowledge of energy sector operations, data flows, and business processes, while being adept at applying this industry insight to support data-driven decision-making. The successful candidate will bridge the gap between technical data management and energy sector strategy, enabling the organization to leverage data as a critical asset.

As a Data Engineer , you’ll be part of an Agile and skilled team of other engineers and analysts working on delivering best in class data solutions for our customers. Working with powerful data processing technologies, you will combine the power of your industry knowledge and industry data flows with the full capabilities of AWS, creating the ultimate data services platform.

Responsibilities

• Work as part of a cross-functional team to design, develop and deploy complex data solutions.

• Provide expert technical advice and recommend solutions to the development resources in the planning, strategizing, and the execution of high profile and complex data processing initiatives.

• Consistently develop with performance in mind to optimize end user experience.

• Work with architects and senior team members to identify new tools and technologies where applicable to expand customer offerings.

• Research and take advantage of new technology to improve and expand solutions.

• Participate in peer code reviews, troubleshoot and correct software defects.

• Work with the internal testing team to ensure appropriate testing is built into the development and ongoing delivery.

• Develop efficient queries to retrieve appropriate datasets from relational databases

• Design, implement and maintain performance of reliable data pipelines and integrations that feed various applications, using both structured and unstructured data

• Create, implement, and maintain data transformation processes

Skills & Knowledge you will need:

• Proven experience in the energy sector with a focus on data-driven projects

• Strong understanding of energy industry concepts, terminology, and key performance indicators.

• Energy Industry Knowledge, specifically around D-Flows their purpose and content.

• Familiarity with data analysis tools and visualization platforms (e.g., Power BI, Tableau) is a plus, but core technical programming skills are secondary to industry knowledge.

• SQL coding skills.

• Ability to translate complex energy data sets into actionable insights for non-technical stakeholders.

• Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams.

• Experience with cloud computing such as Azure or AWS


Nice to have:

• Experience in data modelling.

• Experience of working with large datasets.

• Experience with cloud computing such as Azure or AWS

• SDLC or Product Development experience

• Pentaho Experience

• Knowledge of BI tools such as Tableau

• Python in Data Engineering Experience

• Vertica Experience

• Experience with developing REST APIs and microservices

• Experienced in relational database design

Priyanka Sharma

Senior Delivery Consultant

Office:

Email:

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.