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

Apply Now

Lead Architect

Mastek
London
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Senior/Lead Data Engineer

Job Title: Lead Architect

Location: London, UK (3 days a week in office)

SC Cleared/Eligibility: Required

Job Type: Full-Time

Experience: 11+ Years (Relevant exp 10+ years)

Job Overview:

We are seeking a highly skilled and experienced Lead Architect to play a pivotal role in the design, development, and maintenance of our cutting-edge Azure Databricks data platform for handling economic data. This role will be instrumental in establishing a robust and scalable data and analytics platform that supports critical business functions, including Monetary Analysis, Forecasting, and Modelling.

The successful candidate will possess a deep understanding of data management and engineering principles, cloud computing technologies (specifically Azure and Databricks), and a strong foundation in economic data analysis. You will be responsible for leading the technical vision and roadmap for the platform, ensuring its openness, reusability, and compatibility across various modelling runtimes such as Python, R, and MATLAB, all seamlessly supported by the Databricks environment.


Responsibilities:

  • Platform Architecture & Design:
  • Define and document the overall architecture of the Azure and Databricks platform, encompassing data ingestion, transformation, storage, processing, and consumption.
  • Design and implement robust, configurable and scalable data pipelines for ingesting, cleaning, transforming, and loading economic data from diverse sources (e.g., APIs, databases, financial data providers).
  • Develop and maintain specifications and documentation for data transformations, ensuring consistency and ease of use across different modelling runtimes.
  • Integrate various data sources and tools into the Databricks platform.
  • Modelling Runtime Support:
  • Ensure seamless integration and support for Python, R, and MATLAB modelling runtimes within the Databricks environment.
  • Develop and maintain libraries, frameworks, and tools to facilitate model development, deployment, and monitoring across different runtimes.
  • Optimise data processing and model execution performance within the Databricks environment.
  • Data Governance & Quality:
  • Establish and enforce data quality standards and best practices throughout the data lifecycle.
  • Implement data lineage tracking and provenance to ensure data traceability and auditability.
  • Develop and maintain data security and access control mechanisms to protect sensitive data.
  • Team Leadership & Collaboration:
  • Mentor and guide junior data engineers and analysts on best practices in data engineering and cloud computing.
  • Collaborate closely with data scientists, economists, and business stakeholders.
  • Stay abreast of the latest advancements in cloud computing, data engineering, and economic data analysis.
  • Innovation & Continuous Improvement:
  • Identify opportunities to improve platform performance, scalability, and efficiency.
  • Research and evaluate emerging technologies and tools.
  • Drive innovation in the use of data and technology to support business objectives.


Qualifications/Skills:

  • 10+ years of proven experience as a Lead Architect or a similar senior technical role in a data-driven environment, with at least 5+ years specifically focused on Azure cloud solutions.
  • Deep understanding of data engineering principles, including data warehousing, data modelling, data integration, and data quality.
  • Extensive experience with Azure Databricks, including data pipelines, Delta Lake, and other relevant services (minimum 3 years hands-on experience).
  • Strong proficiency in Python and experience with other programming languages (e.g., R, Scala, .NET).
  • Experience with API development and integration, including RESTful APIs and API documentation standards.
  • Familiarity with economic data analysis concepts and methodologies.
  • Experience with Agile development methodologies and DevOps practices.
  • Excellent communication, interpersonal, and presentation skills.
  • Strong analytical and problem-solving skills.
  • Ability to work independently and as part of a team.
  • Active Azure Certifications: At least one of the following is required:
  • Azure Solutions Architect Expert
  • Azure Data Engineer Associate

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

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.

Jobs

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.

Jobs

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.

🍪 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.