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Data Engineer

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Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

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The role sits within the Chief Data Office (CDO) and reports to the Data Engineering Manager, with technical oversight and guidance provided by a Lead Data Engineer.

The Data Engineer is responsible for designing, developing, testing, deploying, and supporting data solutions that enable trusted, timely, and accessible data across the organisation.

  • Design, develop, test, and maintain data pipelines, integrations, and data products across the enterprise data platform.

  • Develop and maintain solutions using Azure Data Factory, Azure Data Lake Storage, Databricks, Delta Lake, Azure Key Vault, and related Azure technologies.

  • Maintain source control and deployment processes using Azure DevOps and Git-based workflows.

From the employer’s posting
The role sits within the Chief Data Office (CDO) and reports to the Data Engineering Manager, with technical oversight and guidance provided by a Lead Data Engineer.
The Data Engineer is responsible for designing, developing, testing, deploying, and supporting data solutions that enable trusted, timely, and accessible data across the organisation. The role supports Quilter's data strategy by delivering scalable, secure, and resilient data products and services that underpin reporting, analytics, regulatory obligations, operational processes, and digital capabilities.
Data Solution Development Design, develop, test, and maintain data pipelines, integrations, and data products across the enterprise data platform. Build scalable and reusable solutions for data ingestion, transformation, enrichment, and consumption.
Data Platform Engineering Develop and maintain solutions using Azure Data Factory, Azure Data Lake Storage, Databricks, Delta Lake, Azure Key Vault, and related Azure technologies. Support the ongoing enhancement of platform capabilities, standards, frameworks, and reusable components.
Follow established engineering standards, coding practices, and architectural principles. Maintain source control and deployment processes using Azure DevOps and Git-based workflows. Create and maintain automated testing and validation processes.

About Quilter

Our foundations are rooted in our extraordinary expertise, which is trusted by hundreds of thousands of customers, but we have great ambitions to stay one step ahead and make an even greater difference to the people and communities we serve, including our colleagues.

In the employer’s words · Read in context

Apply at Quilter

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 13, 2026today
Recorded sightings
1

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How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 56.

At Quilter, jobs usually come down by about day 27.

From 13,649 similar postings that came down, and 13 of Quilter’s. Coming down is not always a hire.

Quilter is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
  • 25% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Scala
  • SQL
  • Azure
  • Databricks
  • Delta Lake
Where the posting names them
·Spark: Good understanding of distributed processing concepts, Spark performance optimisation, partitioning, and workload tuning. ·Languages: Strong SQL and Python development skills; experience with additional languages such as Scala is desirable. ·CI/CD & DevOps: Azure DevOps, Git-based development practices, automated deployments, testing frameworks, and Infrastructure as Code concepts.
The Data Engineer is responsible for designing, developing, testing, deploying, and supporting data solutions that enable trusted, timely, and accessible data across the organisation. The role supports Quilter's data strategy by delivering scalable, secure, and resilient data products and services that underpin reporting, analytics, regulatory obligations, operational processes, and digital capabilities. Working within Agile delivery teams, the Data Engineer collaborates with Product Owners, Business Analysts, Data Analysts, Architects, platform teams, and business stakeholders to transform data requirements into high-quality engineering solutions. The role contributes to the continuous evolution of Quilter's cloud-based data platform, leveraging technologies including Azure Data Factory, Azure Data Lake Storage, Databricks, Azure Key Vault, Azure DevOps, and related Azure services. The successful candidate will demonstrate strong technical capability, a proactive approach to problem solving, a commitment to engineering excellence, and a focus on delivering business value through data.
Data Platform Engineering - Develop and maintain solutions using Azure Data Factory, Azure Data Lake Storage, Databricks, Delta Lake, Azure Key Vault, and related Azure technologies. - Support the ongoing enhancement of platform capabilities, standards, frameworks, and reusable components.
- Follow established engineering standards, coding practices, and architectural principles. - Maintain source control and deployment processes using Azure DevOps and Git-based workflows. - Create and maintain automated testing and validation processes.
- Identify opportunities to improve engineering practices, tooling, automation, and delivery processes. - Stay current with developments across Azure, Databricks, data engineering, and cloud technologies. - Contribute ideas and recommendations to improve platform efficiency, reliability, and scalability.
· Degree in a technical discipline (e.g. Computer Science, Engineering, Mathematics, Physics) or evidence of equivalent practical experience. · Relevant industry certifications in Azure, Databricks, Data Engineering, or cloud technologies are desirable but not essential. Knowledge & Experience
·Proven experience as a Data Engineer delivering data pipelines, data integrations, and data products within a cloud-based enterprise environment. ·Hands-on experience designing, developing, testing, and supporting data solutions using Databricks within Azure. ·Experience developing batch and near real-time data processing solutions using modern data engineering technologies and patterns.
·Microsoft Fabric: Awareness of Lakehouse, Data Warehouse, Real-Time Intelligence, Semantic Models, and Fabric engineering concepts. ·Azure: ADLS Gen2, Azure Data Factory, Azure Key Vault, Azure Monitor, Functions, and broader Azure data services. ·Spark: Good understanding of distributed processing concepts, Spark performance optimisation, partitioning, and workload tuning.
·Languages: Strong SQL and Python development skills; experience with additional languages such as Scala is desirable. ·CI/CD & DevOps: Azure DevOps, Git-based development practices, automated deployments, testing frameworks, and Infrastructure as Code concepts. ·Orchestration: Databricks Workflows, Azure Data Factory, Fabric Pipelines, and enterprise scheduling frameworks.
·CI/CD & DevOps: Azure DevOps, Git-based development practices, automated deployments, testing frameworks, and Infrastructure as Code concepts. ·Orchestration: Databricks Workflows, Azure Data Factory, Fabric Pipelines, and enterprise scheduling frameworks. ·Data Architecture & Modelling: Understanding of dimensional modelling, Data Vault concepts, medallion architecture, and lakehouse design approaches.
·Strong communication and collaboration skills with the ability to work effectively within cross-functional teams. ·Databricks: Delta Lake, Unity Catalog, Workflows, Notebooks, Asset Bundles, Delta Live Tables, Spark Declarative Pipelines, and platform optimisation principles. ·Microsoft Fabric: Awareness of Lakehouse, Data Warehouse, Real-Time Intelligence, Semantic Models, and Fabric engineering concepts.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

About the Business

Quilter plc is a leading wealth management business, helping to enable brighter financial futures for every generation.

Quilter oversees £160.5 billion in customer investments (as of September 2026). It has an adviser and customer offering spanning financial advice, investment platforms, multi-asset investment solutions, and discretionary fund management. The business is comprised of two segments: Affluent and High Net Worth.

Affluent encompasses the financial planning business, Quilter Financial Planning, the Quilter Investment Platform and Quilter Investors, the multi-asset investment solutions business.

High Net Worth includes the discretionary fund management business, Quilter Cheviot, together with Quilter Cheviot Financial Planning – offering a highly personalised service to private clients, charities, trustees, and professional partners. Quilter Cheviot has presence throughout the UK, Ireland and Channel Islands.

At Quilter we never stand still. Our foundations are rooted in our extraordinary expertise, which is trusted by hundreds of thousands of customers, but we have great ambitions to stay one step ahead and make an even greater difference to the people and communities we serve, including our colleagues.

Our business is transforming, continually modernising, and becoming even more customer centric. So, if you want to be bold in the pursuit of your ambitions, bring new ideas, and challenge and evolve what we do, it’s the perfect time to join us!

About the Role

Level: 4

Department: COO

Location: Southampton or London

Contract type: Permanent

 

The role sits within the Chief Data Office (CDO) and reports to the Data Engineering Manager, with technical oversight and guidance provided by a Lead Data Engineer.

 

The Data Engineer is responsible for designing, developing, testing, deploying, and supporting data solutions that enable trusted, timely, and accessible data across the organisation. The role supports Quilter's data strategy by delivering scalable, secure, and resilient data products and services that underpin reporting, analytics, regulatory obligations, operational processes, and digital capabilities.

 

Working within Agile delivery teams, the Data Engineer collaborates with Product Owners, Business Analysts, Data Analysts, Architects, platform teams, and business stakeholders to transform data requirements into high-quality engineering solutions. The role contributes to the continuous evolution of Quilter's cloud-based data platform, leveraging technologies including Azure Data Factory, Azure Data Lake Storage, Databricks, Azure Key Vault, Azure DevOps, and related Azure services.

 

The successful candidate will demonstrate strong technical capability, a proactive approach to problem solving, a commitment to engineering excellence, and a focus on delivering business value through data.

 

Key Accountabilities

 

Data Solution Development

  • Design, develop, test, and maintain data pipelines, integrations, and data products across the enterprise data platform.
  • Build scalable and reusable solutions for data ingestion, transformation, enrichment, and consumption.
  • Develop and optimise batch, near real-time, and streaming data processing solutions where required.
  • Ensure solutions are robust, performant, secure, and maintainable.
  • Contribute to the delivery of analytical, operational, and regulatory data capabilities.

 

Data Platform Engineering

  • Develop and maintain solutions using Azure Data Factory, Azure Data Lake Storage, Databricks, Delta Lake, Azure Key Vault, and related Azure technologies.
  • Support the ongoing enhancement of platform capabilities, standards, frameworks, and reusable components.
  • Implement infrastructure and configuration changes through automated deployment processes.
  • Contribute to platform modernisation initiatives and technology adoption activities.

 

Engineering Standards & Quality

  • Follow established engineering standards, coding practices, and architectural principles.
  • Maintain source control and deployment processes using Azure DevOps and Git-based workflows.
  • Create and maintain automated testing and validation processes.
  • Participate in code reviews and peer reviews to promote quality, consistency, and knowledge sharing.
  • Ensure solutions are appropriately documented and supportable.

 

Data Governance, Security & Risk Management

  • Apply data governance, security, privacy, and retention requirements throughout the engineering lifecycle.
  • Ensure data solutions comply with internal policies, regulatory obligations, and security standards.
  • Support implementation of role-based access controls, data classification requirements, and auditability standards.
  • Contribute to maintaining accurate metadata, lineage, and data quality controls.
  • Identify and escalate operational, security, and data risks where appropriate.

 

Operational Support & Reliability

  • Monitor and support production data products and services.
  • Investigate and resolve incidents, defects, and performance-related issues.
  • Participate in root cause analysis activities and implement preventative improvements.
  • Support service resilience through monitoring, alerting, automation, and operational best practices.
  • Contribute to capacity planning, performance tuning, and cost optimisation activities.

 

Stakeholder Collaboration

  • Work closely with Product Owners, Analysts, Architects, Platform Engineers, and business stakeholders to understand requirements and priorities.
  • Interpret business requirements and translate them into technical solutions.
  • Provide updates on delivery progress, risks, issues, and dependencies.
  • Support user adoption by ensuring solutions are reliable, well-documented, and aligned with business needs.

 

Continuous Improvement & Innovation

  • Identify opportunities to improve engineering practices, tooling, automation, and delivery processes.
  • Stay current with developments across Azure, Databricks, data engineering, and cloud technologies.
  • Contribute ideas and recommendations to improve platform efficiency, reliability, and scalability.
  • Participate in knowledge sharing, technical communities, and continuous learning activities.

 

 

About You

Qualifications


· Degree in a technical discipline (e.g. Computer Science, Engineering, Mathematics, Physics) or evidence of equivalent practical experience.

· Relevant industry certifications in Azure, Databricks, Data Engineering, or cloud technologies are desirable but not essential.

 

Knowledge & Experience

·Proven experience as a Data Engineer delivering data pipelines, data integrations, and data products within a cloud-based enterprise environment.

·Hands-on experience designing, developing, testing, and supporting data solutions using Databricks within Azure.

·Experience developing batch and near real-time data processing solutions using modern data engineering technologies and patterns.

·Experience building and maintaining scalable, reliable, and secure data pipelines that support reporting, analytics, data science and operational use cases.

·Understanding of data quality, validation, monitoring, and observability concepts and their application within data engineering solutions.

·Knowledge of data governance principles, including data lineage, metadata management, security, and access control practices.

·Experience working within regulated environments and applying data protection, information security, and data retention requirements.

·Experience applying engineering standards and development best practices including source control, testing, automation, and CI/CD.

·Experience contributing to code reviews, peer reviews, and collaborative engineering activities.

· Knowledge of data modelling concepts, including dimensional modelling, lakehouse architectures, and modern data platform design principles.

·Experience working within Agile delivery teams and collaborating with architects, analysts, product owners, platform teams, and business stakeholders.


Skills

·Strong technical and analytical skills with the ability to develop high-quality, maintainable, and scalable data solutions.

·Excellent problem-solving capabilities with a structured approach to troubleshooting and resolving technical issues.

·Strong communication and collaboration skills with the ability to work effectively within cross-functional teams.

·Databricks: Delta Lake, Unity Catalog, Workflows, Notebooks, Asset Bundles, Delta Live Tables, Spark Declarative Pipelines, and platform optimisation principles.

·Microsoft Fabric: Awareness of Lakehouse, Data Warehouse, Real-Time Intelligence, Semantic Models, and Fabric engineering concepts.

·Azure: ADLS Gen2, Azure Data Factory, Azure Key Vault, Azure Monitor, Functions, and broader Azure data services.

·Spark: Good understanding of distributed processing concepts, Spark performance optimisation, partitioning, and workload tuning.

·Languages: Strong SQL and Python development skills; experience with additional languages such as Scala is desirable.

·CI/CD & DevOps: Azure DevOps, Git-based development practices, automated deployments, testing frameworks, and Infrastructure as Code concepts.

·Orchestration: Databricks Workflows, Azure Data Factory, Fabric Pipelines, and enterprise scheduling frameworks.

·Data Architecture & Modelling: Understanding of dimensional modelling, Data Vault concepts, medallion architecture, and lakehouse design approaches.

·Data Governance & Security: Understanding of secure-by-design principles, data governance controls, access management, and operational monitoring practices.

 

Desired Attributes

·Passionate about data engineering, technology, and continuous learning.

·Demonstrates a proactive approach to problem solving and continuous improvement.

·Takes ownership of work deliverables and follows tasks through to completion.

·Collaborative team player who values knowledge sharing and constructive feedback.

·Committed to delivering high-quality, reliable, and supportable engineering solutions.

·Curious and adaptable, with a desire to learn new technologies, tools, and engineering practices.

·Balances technical excellence with a pragmatic, delivery-focused mindset.

·Demonstrates attention to detail and a strong appreciation for data quality, security, and governance.

 

#LI-PM1

 

Inclusion & Diversity

We value diversity and strive to promote inclusivity in all aspects of our culture. We believe in equal opportunities for all, ensuring that no applicant encounters less favourable treatment based on anything but their skills, qualifications, experience, and potential. We celebrate the unique contributions of a diverse workforce and create a respectful, nurturing environment where every colleague can thrive.

Values

Do the right thing: We act with integrity and are proudly committed to going above and beyond in service of our clients and the support we provide our communities.
Always curious: We continuously seek new ideas and knowledge so we’re one step ahead of our clients’ needs. We look for inspiration everywhere and encourage experimentation, recognising that this is how we create brilliant solutions for brighter futures.
Embrace challenge: We aim high to transform our potential into meaningful outcomes. With ambition as our driving force and a steadfast commitment to growth, we succeed for the good of every generation.
Stronger together: Combining our diverse talents, we accomplish more collectively than we ever could do alone. We speak openly, actively listen, and support each other, and constructively challenge and embrace new ideas. We seek empowerment and demonstrate ownership and trust, with the confidence to make impactful decisions.

Core Benefits

Holiday: 182 hours (26 days)

Quilter Incentive Scheme: All employees are eligible to participate in incentive scheme, to incentivise business performance and their contribution.

Pension Scheme: A non-contributory company pension scheme that can be boosted through personal contributions.

Private Medical Insurance: Single cover as standard with options to increase cover to include your partner or children.

Life Assurance: 4x your salary.

Income Protection: 75% of salary, less state benefits, payable after 26 weeks of absence.

Healthcare Cash Plan: Jersey employees only

In addition to our core benefits, we offer a range of flexible benefits to UK employees that you can choose from and pay for conveniently via a salary deduction.

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