Senior Backend Engineer - Data Engineer

St James's
1 month ago
Create job alert

Our Energy client seeks a Senior Backend Engineer - Data Engineer to join their team in Mayfair, London.

We are looking for a Senior Backend Software Engineer with strong data engineering skills to join a small, agile team developing software solutions for our energy supply and trading functions.

Hybrid working is in play, with 3 days in the office and 2 days at home.

Senior Backend Engineer - Data Engineer - About the role:

My client’s energy business is growing rapidly with a strong focus on using advanced data systems and analytics to deliver exceptional service. We are looking for someone to take ownership of the backend architecture that underpins our analytics applications, user tools, and automated trading workflows.

You will collaborate closely with analysts, data scientists, and business stakeholders to translate requirements into robust, scalable backend solutions. You’ll be responsible for designing and developing services, APIs, data pipelines, and internal applications that integrate analytics and enable better decision-making and operational efficiency.

This is a hands-on role for someone who thrives in a fast-paced, build-first culture without multiple tiers of management. You should be excited to take full ownership of backend development, lead on best practices, and coach others in a collaborative, delivery-focused team.

Experience in retail or wholesale electricity and gas markets is helpful, but a willingness to become an expert in this field is essential. Our success is based on understanding the subject matter from first principles.

Senior Backend Engineer - Data Engineer - Key Responsibilities:

  • Architect, design, develop and maintain backend systems for analytics-driven applications, user tools, and automation workflows.

  • Build and manage APIs and internal services using Python (FastAPI, Flask) and cloud-native tooling.

  • Develop and manage data pipelines, backend components, and supporting infrastructure.

  • Manage server resources and backend processing environments to ensure reliability and scalability.

  • Monitor and maintain application performance, availability, and data quality across production systems.

  • Implement and maintain CI/CD pipelines, testing frameworks, and DevOps practices to enable robust delivery.

  • Write, test, and document code in line with quality standards and engineering best practices.

  • Collaborate with operations, analytics and commercial teams to gather requirements and translate them into scalable technical solutions.

  • Support analysts and data scientists in deploying and operationalising analytics tools and models.

  • Lead or support the data engineering team, help structure development workflows, and mentor junior team members.

  • Stay current with technological advancements and promote a culture of continuous improvement.

  • Present technical solutions to stakeholders and train non-technical users on tools and workflows.

    Senior Backend Engineer - Data Engineer - Skills Required:

  • Python (FastAPI, Flask)

  • REST API development

  • Containerisation: Docker, Kubernetes

  • CI/CD: Azure DevOps, GitHub Actions

  • Software testing and documentation practices

  • SQL, PySpark, Databricks

  • Relational databases and data lake architecture

  • Model and data pipeline integration (e.g. MLflow)

  • Streamlit or other lightweight UI frameworks

  • Microsoft Azure (Functions, Storage, Compute)

  • Monitoring tools (Grafana, Prometheus, etc.)

  • Performance optimisation and resource management

  • Agile delivery practices (Jira, Azure Boards, etc.)

  • Strong communication with technical and business teams

  • Mentoring and knowledge sharing within the team

    Desirable Skills:

  • Experience in energy supply or trading

  • Familiarity with dbt or modular analytics tooling

  • Exposure to forecasting or optimisation workflows

  • Knowledge of React or frontend tools for internal apps

  • Networking or IoT integration experience

    What they offer:

  • A high-autonomy role in a flat, delivery-focused team

  • Ownership of backend systems for real-time analytics and automation

  • A fast-moving, hands-on culture with meaningful technical challenges

  • The opportunity to apply software and data engineering to real-world energy problems

Related Jobs

View all jobs

Senior Backend Engineer - Data Engineer

Software Engineer

Senior Data Engineer

Group Finance Business Partner

Senior Data Engineer Python Spark SQL

Data Engineering Manager

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

Data Science Jobs in the Public Sector: Exploring Opportunities Across GDS, NHS, MOD, and More

Data science has emerged as one of the most influential fields in the 21st century, transforming how organisations make decisions, improve services, and solve complex problems. Nowhere is this impact more visible than in the UK public sector. From the Government Digital Service (GDS) to the National Health Service (NHS) and the Ministry of Defence (MOD), government departments and agencies handle vast amounts of data daily to support the well-being and security of citizens. For data enthusiasts looking to make a meaningful contribution, data science jobs in the public sector can offer rewarding roles that blend innovation, large-scale impact, and societal benefit. In this comprehensive guide, we’ll explore why data science is so pivotal to government, the roles you might find, the skills needed, salary expectations, and tips on how to succeed in a public sector data science career.