National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Engineer ›

Aztec
London
3 days ago
Create job alert

At the Aztec Group we credit our technology as one of the core ingredients to our award-winning outsourced solutions. As part of its Five-Year Plan, Aztec has the ambition to be a market-leading alternative fund administrator that provides compelling client experiences, products, and services.
These are exciting times across the group. Significant growth, change, and investment make it a truly world-class opportunity to help shape our organisation for the next stage of its journey.
To drive towards this ambition, we are seeking a motivated individual to join our Data Platform team and support Aztec’s new technology strategy using Azure Databricks. You will lead our Data Engineering capability and collaborate with others passionate about solving business problems.
Key responsibilities:
Data Platform Design and Architecture
Design, develop, and maintain a high-performing, secure, and scalable data platform, leveraging Databricks Corporate Lakehouse and Medallion Architectures.
Utilise our metadata-driven data platform framework combined with advanced cluster management techniques to create and optimise scalable, robust, and efficient data solutions.
Implement comprehensive logging, monitoring, and alerting tools to manage the platform, ensuring resilience and optimal performance are maintained.
Data Integration and Transformation
Integrate and transform data from multiple organisational SQL databases and SaaS applications using end-to-end dependency-based data pipelines, to establish an enterprise source of truth.
Create ETL and ELT processes using Azure Databricks, ensuring audit-ready financial data pipelines and secure data exchange with Databricks Delta Sharing and SQL Warehouse endpoints.
Governance and Compliance
Ensure compliance with information security standards in our highly regulated financial landscape by implementing Databricks Unity Catalog for governance, data quality monitoring, and ADLS Gen2 encryption for audit compliance.
Development and Process Improvement
Evaluate requirements, create technical design documentation, and work within Agile methodologies to deploy and optimise data workflows, adhering to data platform policies and standards.
Collaboration and Knowledge Sharing
Collaborate with stakeholders to develop data solutions, maintain professional knowledge through continual development, and advocate best practices within a Centre of Excellence.
Skills, knowledge and expertise:
Deep expertise in the Databricks platform, including Jobs and Workflows, Cluster Management, Catalog Design and Maintenance, Apps, Hive Metastore Management, Network Management, Delta Sharing, Dashboards, and Alerts.
Proven experience working with big data technologies, i.e., Databricks and Apache Spark.
Proven experience working with Azure data platform services, including Storage, ADLS Gen2, Azure Functions, Kubernetes.
Background in cloud platforms and data architectures, such as Corporate DataLake, Medallion Architecture, Metadata Driven Platform, Event-driven architecture.
Proven experience of ETL/ELT, including Lakehouse, Pipeline Design, Batch/Stream processing.
Strong working knowledge of programming languages, including Python, SQL, PowerShell, PySpark, Spark SQL.
Good working knowledge of data warehouse and data mart architectures.
Good experience in Data Governance, including Unity Catalog, Metadata Management, Data Lineage, Quality Checks, Master Data Management.
Experience using Azure DevOps to manage tasks and CI/CD deployments within an Agile framework, including utilising Azure Pipelines (YAML), Terraform, and implementing effective release and branching strategies.
Knowledge of security practices, covering RBAC, Azure Key Vault, Private Endpoints, Identity Management.
Experience working with relational and non-relational databases and unstructured data.
Exposure to Azure Purview, Power BI, and Profisee is an advantage.
Ability to compile accurate and concise technical documentation.
Strong analytical and problem-solving skills.
Good interpersonal and communication skills.
We will provide the training, both in house for relevant technical knowledge and for professional qualifications. You will need to be quick to learn new systems and be great with people, as close working relationships between our colleagues and clients is at the heart of what we do.
Beyond that, we will be with you every step of the way, enabling you to get the most out of your role, grow your skills your way, and see your career develop in the way you want. Be part of our talented Technology team and unbox your passion at a multi-award-winning leader in the alternative fund management industry.

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - dbt, Snowflake, AWS, Airflow

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.