Data Engineer

Leonardo
Edinburgh
1 week ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Location: Edinburgh, Scotland, United Kingdom


Contract: Permanent, Hybrid


Data Engineer
Job Description

As a Data Engineer, you will design, develop, deploy, and maintain data architecture which employs various methods to transform raw data into processed data. You will own the data operations infrastructure, manage and optimise performance, reliability, and scalability of the system to meet growing demands on ingestion and processing pipelines.


Responsibilities

  • Orchestrate ingestion and storage of raw data into structured or unstructured solutions.
  • Design, develop, deploy, and support data infrastructure, pipelines and architecture.
  • Implement reliable, scalable, and tested solutions to automate data ingestion.
  • Develop systems to manage batch processing and real-time streaming of data.
  • Evaluate business needs and objectives.
  • Support implementation of data governance requirements.
  • Facilitate pipelines that prepare data for prescriptive and predictive modelling.
  • Work with domain teams to scale the processing of data.
  • Identify opportunities for data acquisition.
  • Combine raw information from different sources.
  • Manage and maintain automated tools for data quality and reliability.
  • Explore ways to enhance data quality and reliability.
  • Collaborate with data scientists, IT and architects on several projects.

Qualifications

  • Technical expertise in designing, building, and maintaining data pipelines, data warehouses, and leveraging data services.
  • Proficient in DataOps methodologies and tools, including CI/CD pipelines, containerisation, and workflow orchestration.
  • Experience with ETL/ELT frameworks, and Big Data Processing Tools (e.g., Spark, Airflow, Hive).
  • Knowledge of programming languages (e.g., Java, Python, SQL).
  • Hands‑on experience with SQL/NoSQL database design.
  • Degree in STEM or similar field; a Master’s is a plus.
  • Data engineering certification (e.g., IBM Certified Data Engineer) is a plus.

Security Clearance

This role is subject to pre‑employment screening in line with the UK Government’s Baseline Personnel Security Standard (BPSS). All successful applicants must be eligible for full security clearance and access to UK‑controlled and ITAR‑controlled information. For more information and guidance, please visit https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearance-levels.


Benefits

  • Enjoy generous leave with the opportunity to accrue up to 12 additional flexi‑days each year.
  • Benefit from our award‑winning pension scheme with up to 15% employer contribution.
  • Free access to mental health support, financial advice, and employee‑led networks championing inclusion and diversity.
  • All employees at management level and below are eligible for our bonus scheme.
  • Free access to 4,000+ online courses via Coursera and LinkedIn Learning.
  • Receive a financial reward through our referral programme.
  • Spend up to £500 annually on flexible benefits including private healthcare, dental, family cover, tech & lifestyle discounts, gym memberships and more.
  • Flexible hours with hybrid working options (part‑time possibilities achievable with discussion).


#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.

Education

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

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.

Jobs Careers

Data Engineering Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data engineering in your 30s, 40s or 50s? You’re not alone. In the UK, companies of all sizes — from fintechs to government agencies, retailers to healthcare providers — are building data teams to turn vast amounts of information into insight and value. That means demand for data engineering talent remains strong, but there’s a gap between media hype and the real pathways available to mid-career professionals. This guide gives you the straight UK reality check: which data engineering roles are genuinely open to career switchers, what skills employers actually look for, how long retraining really takes and how to position your experience for success.

Jobs

How to Write a Data Engineering Job Ad That Attracts the Right People

Data engineering is the backbone of modern data-driven organisations. From analytics and machine learning to business intelligence and real-time platforms, data engineers build the pipelines, platforms and infrastructure that make data usable at scale. Yet many employers struggle to attract the right data engineering candidates. Job adverts often generate high application volumes, but few applicants have the practical skills needed to build and maintain production-grade data systems. At the same time, experienced data engineers skip over adverts that feel vague, unrealistic or misaligned with real-world data engineering work. In most cases, the issue is not a shortage of talent — it is the quality and clarity of the job advert. Data engineers are pragmatic, technically rigorous and highly selective. A poorly written job ad signals immature data practices and unclear expectations. A well-written one signals strong engineering culture and serious intent. This guide explains how to write a data engineering job ad that attracts the right people, improves applicant quality and positions your organisation as a credible data employer.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.