Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Engineer

Bridge
Leeds
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

This range is provided by Bridge. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.


Base pay range

Direct message the job poster from Bridge


Senior Recruitment Consultant at Morson Edge
Purpose of the Job

  • Design, build, and maintain robust data systems and pipelines that support data storage, processing, and analysis on the Cloud.
  • Work with large datasets, ensuring data quality, scalability, and performance, while collaborating.

Key Accountabilities

  • Design and implement scalable, efficient, and secure data architectures, ensuring optimal data flow across systems in order to achieve high service levels of support, maintenance and development.
  • You will own development and change projects to ensure requirements are met in the most cost-effective manner while minimising associated risk to expected standards.
  • Responsible for cloud data platform development, data modelling, shaping and technical planning.
  • You will be a mentor among the owning decision making and evaluation of requirement suitability, facilitate reliable estimates, technical project management, stakeholder management with a project.
  • Ensure that resource requirements are understood and planned/estimated effectively against demand, including identification of additional temporary resource capability within projects.
  • Maintain appropriate process procedures, compliance and service level monitoring, performance reporting and vendor management.
  • Implementing best practices around data security, privacy, and compliance for the teams compliance with cyber security and data protection and supporting along with BI lead.
  • Strong stakeholder management will be required for maintaining relationships with our business users to clarify and influence requirements. Including liaising with internal business departments and functions to manage the service level expected from the data team.
  • Mentor data engineers, supporting their professional growth and development.

Knowledge

  • Broad data management technical knowledge so as to be able to work across full data cycle.
  • Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD.
  • Coding experience in Apache Spark, Iceberg or Python (Pandas).
  • Experience in change and release management.
  • Experience in Database Warehouse design and data modelling.
  • Experience managing Data Migration projects.
  • Cloud data platform development and deployment.
  • Experience of performance tuning in a variery of database settings.
  • Experience of Infrastructure as code practices.
  • Proven ability to organise and produce work within deadlines.

Skills

  • Good project and people management skills.
  • Excellent data manipulation and analysis skills using a variety of tools including SQL, Phyton, AWS services and the MSBI stack.
  • Ability to prioritise and be flexible to change those priorities at short notice.
  • Able to provide appropriate and understandable data to a wide ranging audience.
  • Well-developed and professional communication skills.
  • Strong analytical skills - ability to create models and analyse data in order to solve complex problems or reinforce commercial decisions.
  • Able to understand business processes and how this is achieved/influenced by technology.
  • Must be able to work as part of a collaborative team to solve problems and assist other colleagues.
  • Ability to learn new technologies, programs and procedures.

Technical Essentials

  • Expertise across data warehouse and ETL/ ELT development in AWS preferred with experience in the following:
  • Strong experience in some of the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB.
  • Good experience with DBT, Apache Iceberg, Docker, Microsoft BI stack (nice to have).
  • Experience in data warehouse design (Kimball and lake house, medallion and data vault) is a definite preference as is knowledge of other data tools and programming languages such as Python & Spark and Strong SQL experience.
  • Experience is building Data lake and building CI/CD data pipelines.
  • A candidate is expected to understand and can demonstrate experience across the delivery lifecycle and understand both Agile and Waterfall methods and when to apply these.

Experience

This position requires several years of practical experience in a similar environment. We require a good balance of technical and personal/soft skills so successful candidates can be fully effective immediately.



  • Proven experience in developing, delivering and maintaining tactical and enterprise data management solutions.
  • Proven experience in assessing the impact of proposed changes on production solutions.
  • Proven experience in managing and developing a team of technical experts to deliver business outcomes and meet performance criteria.
  • Exposure to Energy markets, Energy Supply industry sector.
  • Developing and implementing operational processes and procedures.

Seniority level

  • Mid-Senior level

Employment type

  • Full-time

Job function

  • Staffing and Recruiting

Referrals increase your chances of interviewing at Bridge by 2x


Get notified about new Data Engineer jobs in Leeds, England, United Kingdom.



#J-18808-Ljbffr

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.