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

Apply Now

Senior Data Architect - Databricks

Latchmere
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer / Architect

Senior Data Engineer

Senior Data Engineer / Data Architect

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Job Title: Data Architect – Databricks Specialist
Location: Remote (UK-based candidates preferred)
Engagement: Contract - Status determination TBC 
Start Date: ASAP
Sector: Financial Services / Consultancy

About the Role We’re looking for an experienced Data Architect with deep expertise in Databricks to join a high-profile data transformation programme within a leading financial consultancy. You will be instrumental in the design and delivery of a scalable, secure, and high-performing data platform leveraging the Databricks Lakehouse architecture.
This is a critical project where you’ll step into a mature environment, helping to define architectural direction and ensure best practices in data engineering, governance, and performance optimisation.

Key Responsibilities
Lead the architecture and design of a next-gen data platform using Databricks and Delta Lake
Collaborate with stakeholders including data engineers, analysts, and business leads to define data requirements and architecture patterns
Ensure the platform is scalable, secure, and aligned to financial regulatory standards
Develop architectural artefacts (diagrams, documentation, guidelines)
Provide technical leadership and mentorship to engineering teams
Champion best practices in data quality, lineage, governance, and performance tuning
Integrate with a wider Azure ecosystem (e.g. Azure Data Lake, Synapse, Power BI)Required Skills & Experience
Proven experience as a Data Architect in enterprise environments
Extensive hands-on experience with Databricks (including SQL, PySpark, Delta Lake)
Solid background in data warehousing, data lakes, and big data frameworks
Strong knowledge of Azure cloud services, especially in data integration
Experience working in regulated environments (e.g. financial services, insurance, banking)
Excellent communication skills, capable of engaging with technical and non-technical stakeholders alike
Comfortable working in agile, fast-paced delivery environmentsNice to Have
Familiarity with CI/CD pipelines, Infrastructure as Code (e.g. Terraform, ARM)
Exposure to data governance tools like Unity Catalog, Purview, Collibra
Knowledge of data privacy regulations (GDPR, financial compliance)Why Join?
Join a respected financial consultancy at the forefront of data innovation
Work on a greenfield Databricks implementation with high visibility
Collaborate with top-tier engineering and architecture professionals
Long-term potential with future project opportunities

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 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.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.