Lead Data Engineer / Architect – Databricks Active - SC Cleared

Farringdon
2 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer / Architect – Databricks Active - SC Cleared

Data Engineer

Data Engineer

Lead Data Engineer

Lead Data Engineer

Senior Data Engineer

Lead Data Engineer / Architect – Databricks - SC Cleared
SR2 is supporting a critical greenfield transformation programme in the public sector and urgently seeks a hands-on Lead Data Engineer/Architect with deep Databricks experience to help set the direction and strategy for the project.
This is a strategic role for someone who has not only delivered but also led end-to-end Databricks implementations, ideally across multiple programmes. You’ll define the technical architecture, lead Proof of Concepts (PoCs), and build a modern data platform from scratch in a highly visible public-sector environment.
Key Responsibilities:

Act as the technical lead for a new Databricks implementation, working from greenfield through to full production deployment.
Own and deliver streaming and batch data pipelines in Databricks for complex, sensitive use cases.
Define and set architectural standards and delivery roadmaps for the data platform.
Lead PoCs with hyperscalers to assess and select appropriate data services and tooling.
Collaborate with engineering teams, stakeholders, and partners to ensure scalability, performance, and compliance.
Document best practices, decisions, and technical architecture to support future scaling and handover.Essential Experience:

2–3+ years of strong, hands-on Databricks experience, including having led implementations from setup through to production.
Demonstrable track record of delivering greenfield or ground-up data platform builds.
Strong Python skills for data transformation and orchestration.
Deep understanding of modern data architectures, pipelines, and cloud-native solutions – especially AWS.
Able to operate strategically (architecture, direction-setting) and tactically (hands-on engineering).
Active SC Clearance (must be current)

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.

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.

Education Jobs

Maths for Data Engineering Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data engineering jobs in the UK, maths can feel like a vague requirement hiding behind phrases like “strong analytical skills”, “performance mindset” or “ability to reason about systems”. Most of the time, hiring managers are not looking for advanced theory. They want confidence with the handful of maths topics that show up in real pipelines: Rates, units & estimation (throughput, cost, latency, storage growth) Statistics for data quality & observability (distributions, percentiles, outliers, variance) Probability for streaming, sampling & approximate results (sketches like HyperLogLog++ & the logic behind false positives) Discrete maths for DAGs, partitioning & systems thinking (graphs, complexity, hashing) Optimisation intuition for SQL plans & Spark performance (joins, shuffles, partition strategy, “what is the bottleneck”) This article is written for UK job seekers targeting roles like Data Engineer, Analytics Engineer, Platform Data Engineer, Data Warehouse Engineer, Streaming Data Engineer or DataOps Engineer.

🍪 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.