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

Apply Now

Lead Data Engineer - SC Cleared - AWS/Oracle

ZipRecruiter
London
8 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data engineer

Lead Data Engineer

Lead Data Engineer

Job Description

Lead Data Engineer - SC Cleared - AWS/Oracle

SR2 is recruiting for a strategic role with a government client of ours in London. We're looking for a Lead Data Engineer to join a high profile data transformation programme.

We are looking for an experienced Lead Data Engineer with a strong technical background in building Java-based microservices, AWS Glue, Oracle PL/SQL, PySpark, SQL, and Athena to join our team. Additionally, you will lead a team of data engineers and work closely with key client stakeholders to deliver high-quality data solutions that align with business needs.

Experience Required:

  1. 6+ years of hands-on experience in data engineering, with a focus on building cloud-based data platforms.
  2. Strong expertise in developing and deploying Java-based microservices in a cloud environment.
  3. Proven experience with AWS Glue and PySpark to build, schedule, and run ETL/ELT processes at scale.
  4. Proficient in PL/SQL.
  5. Advanced proficiency in SQL for querying and optimizing data in cloud-based environments like AWS Athena or Redshift.

This is a long term rolling contract on an outside IR35 basis.

#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.