Data Bricks Mid Level Developer

Leeds
11 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Data engineer

Databricks Data Engineer

Databricks Data Engineer -London | Up to £100K

DataBricks Data Engineer

Databricks Developer (Mid-Level)

Location: Leeds (Hybrid – in-office once every 2-3 weeks)
Duration: 6 months
IR35 Status: Inside IR35

Job Description

We are looking for a Databricks Developer with mid-level experience to join our team on an exciting project in the financial services/ banking industry. The ideal candidate will have strong technical expertise in Databricks development, hands-on experience with Google Cloud Platform (GCP), and familiarity with platform administration.

Responsibilities

  • Develop, implement, and optimize solutions on the Databricks platform.

  • Work collaboratively with data engineers, analysts, and stakeholders to deliver scalable data solutions.

  • Leverage Google Cloud Platform (GCP) for data integration and management.

  • Troubleshoot, debug, and optimize Databricks workflows and processes.

  • Contribute to platform maintenance and administration as needed.

    Requirements

  • Proven experience as a Databricks Developer, with a focus on developing scalable data solutions.

  • Strong hands-on experience with Google Cloud Platform (GCP).

  • Familiarity with Databricks platform administration is a plus.

  • Experience in financial services or banking is essential.

  • Excellent problem-solving and communication skills

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 Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

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.