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

Apply Now

Data Engineer, Delivery Centre

Credera
Newcastle upon Tyne
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Senior Data Engineer

Senior Data Engineer

Lead Data Engineer - Microsoft Fabric - Hybrid - £75k

Principal Data Engineer

Principal Data Engineer. Job in Glasgow Education & Training Jobs

Job Overview

Data Engineer, Delivery Centre – Credera, Newcastle upon Tyne, United Kingdom. The Delivery Centre provides dedicated engineering capacity for client partnerships, focusing on building microservices architectures, AI and machine learning capabilities, and cloud infrastructure. The central hub for this position is in Newcastle, with opportunities for applicants from across the UK.

Note: This information relates to a specific client requirement. Any offer of employment is subject to satisfactory BPSS and SC security clearance, including a minimum of 5 years’ continuous UK residency and confirmation of holding a British passport at the point of application.

How you will be expected to work

As an Engineer in Credera’s Delivery Centre capability, you’ll work as part of a close-knit team supporting one of our long-term client partnerships alongside architects, support engineers, and delivery leaders. You’ll have the opportunity to learn from a team of experts and develop into a future technical leader.

As a junior delivery centre engineer you will work closely with a senior consulting engineer who will engage with clients directly, typically on site, shape initial problems and translate requirements into technical tasks. You’ll be expected to communicate clearly, act with humility, and work both collaboratively and independently on technical tasks and objectives.

Responsibilities
  • Collaborate with team members to support client engagements within the Delivery Centre
  • Help translate client requirements into technical tasks
  • Contribute to the development and operation of data and analytics platform capabilities
  • Assist with monitoring, logging, and observability of data pipelines and workflows
  • Engage with architects, technology consultants, and client stakeholders as needed
Requirements

You’ll have:

  • The ability to work collaboratively
  • Experience of back-end / data engineering across a number of languages (including Python), and commonly used IDEs
  • Experience with developing, scheduling, maintaining and resolving issues with batch or micro-batch jobs on AWS ETL or Azure ETL services
  • Experience querying data stored on AWS S3 or Azure ADLSv2, or through a Lakehouse capability
  • Experience in managing API-level and database connectivity
  • Experience using source control and DevOps tooling such as Gitlab
  • Experience in use of Terraform (or similar cloud-native products) to build new data & analytics platform capabilities
  • Experience supporting live service within a standard Service Management environment
  • Experience automating operations tasks with one or more scripting languages
  • Experience with developing data features and associated transformation procedures on a modern data platform (e.g., Azure Fabric, AWS Lake Formation, Databricks, Snowflake)
  • Experience in configuring logging, alerts and observability of data jobs and pipelines using AWS or Azure services
  • Experience with relational databases such as PostgreSQL, Oracle DB or MySQL
  • Experience working within a team in an agile, iterative engineering environment
  • A drive for self-improvement and learning new technologies and programming languages
  • Approach to problem solving that is pragmatic
Benefits and culture
  • A highly collaborative working environment and competitive compensation
  • A range of flexible benefits for well-being and lifestyle
  • One-to-one mentoring and hands-on experience for growth
  • Personalised learning and development opportunities
  • 25 days of holiday, with flexibility to up to 30 days
  • 1 CSR volunteering day to give back to the community

Learn More: Credera is a global consulting firm that combines transformational consulting capabilities with AI and technology expertise to deliver valuable customer experiences across industries. Credera is part of the OPMG Group of Companies, a division of Omnicom Group Inc. Credera will never ask for money up front and will not use messaging apps for communicating with you. Be cautious of opportunities that ask for money or require communication exclusively via chat.


#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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.