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.
Employment type in the employer’s posting: Full timeFrom 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.
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.
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.
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
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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.
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
·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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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
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.
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.
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.
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
Data Platform Engineering
Engineering Standards & Quality
Data Governance, Security & Risk Management
Operational Support & Reliability
Stakeholder Collaboration
Continuous Improvement & Innovation
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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Southampton
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