Q

Quilter

Wealth management services and investment solutions

Lead Data Engineer

Data EngineeringPosted on Nov 13
Full-timeNo salary listed

About the Job

Requirements

  • Degree in a technical discipline such as computer science, engineering, mathematics, or physics, or equivalent practical experience.
  • Proven experience as a senior or lead data engineer in a complex enterprise environment delivering large-scale data solutions.
  • Strong hands-on experience designing, developing, and supporting data platforms and pipelines using Databricks within Azure.
  • Experience implementing batch and real-time data processing solutions, including event-driven and streaming architectures.
  • Demonstrable experience leading technical design and delivery of data products and platform capabilities across one or more business domains.
  • Experience implementing and promoting data quality frameworks, service level objectives, data contracts, and observability tooling.
  • Strong understanding of data governance principles, including data lineage, metadata management, cataloguing, security, and access controls.
  • Experience ensuring compliance with regulatory and organisational requirements, including GDPR, data retention, and information security controls.
  • Proven ability to define technical standards, engineering patterns, and best practices and drive their adoption across engineering teams.
  • Experience mentoring and coaching engineers, conducting code reviews, and promoting engineering excellence.
  • Strong experience designing and implementing data models across multiple architectural layers, including Kimball dimensional modelling and Data Vault methodologies.
  • Experience working within Agile delivery teams and collaborating with architects, product owners, analysts, and business stakeholders to deliver business outcomes.
  • Strong technical leadership skills and ability to influence engineering direction and drive best practices across teams.
  • Strategic thinking, analytical capability, curiosity, and commitment to continuous improvement.
  • Problem-solving ability to resolve complex technical challenges and make sound engineering decisions.
  • Ability to communicate complex technical concepts clearly to technical and non-technical audiences.
  • Knowledge of Databricks Delta Lake, Unity Catalog, Workflows, Asset Bundles, Notebooks, Compute Management, Delta Live Tables, Spark Declarative Pipelines, and platform optimisation.
  • Knowledge of Microsoft Fabric Lakehouse, Data Warehouse, Real-Time Intelligence, Semantic Models, and Fabric administration concepts.
  • Knowledge of Azure Data Lake Storage Gen2, Azure Data Factory, Key Vault, Azure Functions, Azure Monitor, and broader Azure data services.
  • Deep understanding of Spark internals, distributed computing principles, optimisation techniques, features, and performance tuning.
  • Advanced Python and SQL development skills.
  • Knowledge of Azure DevOps, Git-based development workflows, Infrastructure as Code, automated testing, and deployment automation.
  • Knowledge of Databricks Workflows, Azure Data Factory, Fabric pipelines, and enterprise scheduling and orchestration frameworks.
  • Knowledge of Kimball, Data Vault, medallion architecture, and modern lakehouse design patterns.
  • Experience implementing secure-by-design data solutions, platform governance controls, and operational monitoring practices.

Responsibilities

  • Provide technical leadership for one or more data domains as the primary engineering authority and subject matter expert.
  • Define, champion, and evolve data engineering standards, patterns, and best practices to ensure robust, efficient, secure, and maintainable solutions.
  • Lead solution design and guide implementation of scalable data pipelines, data products, and platform capabilities.
  • Review code, architecture, and engineering approaches for consistency, quality, and alignment with strategic objectives.
  • Provide hands-on support to resolve complex technical challenges and critical delivery issues.
  • Lead technical delivery of key initiatives and ensure solutions meet business requirements and engineering principles.
  • Translate business and product requirements into technical designs and implementation plans.
  • Collaborate with Data Engineering Managers, Product Owners, Architects, and stakeholders to prioritise and deliver work.
  • Drive adoption of automation, testing, CI/CD, source control, observability, and Infrastructure as Code.
  • Contribute to roadmap planning by identifying technical opportunities, risks, dependencies, and improvement initiatives.
  • Coach, mentor, and provide technical guidance to data engineers across the team.
  • Develop engineering capability through knowledge sharing, technical reviews, pair programming, and communities of practice.
  • Promote a collaborative and inclusive engineering culture focused on quality, learning, and continuous improvement.
  • Model engineering excellence and professional standards.
  • Partner with product managers, analysts, data scientists, platform teams, and business stakeholders to understand requirements and deliver outcomes.
  • Work with architecture, platform, and governance teams to align solutions with enterprise standards and strategic direction.
  • Communicate technical concepts to technical and non-technical audiences.
  • Influence decisions by providing expert technical advice and recommendations.
  • Promote operational stability, reliability, and performance of data products and pipelines through monitoring, alerting, automation, and incident management practices.
  • Champion data quality, security, governance, and regulatory compliance.
  • Identify and implement improvements to platform efficiency, engineering productivity, and service resilience.
  • Support root cause analysis and continuous improvement to enhance operational performance and service reliability.

Desired Qualifications

  • Scala experience is beneficial.
  • Passion for engineering excellence and continuous learning.
  • Acts as a trusted technical advisor and subject matter expert within the domain.
  • Proactively identifies opportunities to improve platform capability, performance, reliability, and security.
  • Collaborative and supportive approach to mentoring others and sharing knowledge.
  • Takes ownership and accountability for technical outcomes while maintaining a pragmatic, delivery-focused approach.

About the Company

Quilter

Wealth management services and investment solutions

Quilter provides wealth management and financial planning services in the United Kingdom. It helps people manage investments, pensions, and savings across the entire investment journey, offering products such as investment portfolios, financial advice, and retirement planning through a broad set of services. The company stands out by serving as a large, established UK provider with a wide range of products tied to every stage of a client’s financial life, aiming to support clients through education and guidance as their money grows. Quilter’s goal is to create brighter financial futures for every generation.

Company size
Not listed
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2007

Recently Posted Jobs

Explore more opportunities at Quilter

See more jobs