Expert Data Engineer

iPipeline
Cheltenham
4 days ago
Create job alert
Overview

As a global market leader, iPipeline combines technology, innovation, and expertise to deliver ground-breaking, award-winning software solutions that transform the life insurance, financial services, and protection industries. With one of the industry’s largest data sets, we help advisors/advisers and agents to transform paper and manual operations into a secure, seamless digital experience – from proposal to commission– so they can help better secure the financial futures of their clients.


At iPipeline, you’ll play a major role in helping us to provide best-in-class, transformative solutions. We’re passionate, creative, and innovative, and together as a team, we continually strive to advance, accelerate, and expand the reach of our technology. We value different perspectives and are committed to creating an environment that embraces diverse backgrounds and fosters inclusion. We’re proud that we’ve been recognized as a repeat winner of various industry awards, demonstrating our excellence and highlighting us as a top workplace in both the US and the UK. We believe that the culture we’ve built for our nearly 900 employees around the world is exceptional -- and we’ve created a place where our employees love to come to work, every single day.


About IPipeline: Founded in 1995, iPipeline operates as a business unit of Roper Technologies (Nasdaq: ROP). iPipeline is a leading global provider of digital solutions for the life insurance and financial services industries in North America, and life insurance and pensions industries in the UK. We couple one of the most expansive digital and automated platforms with one of the industry’s largest data libraries to accelerate, automate, and simplify various applications, processes, and workflows – from quote to commission – with seamless integration. Our vision is to help everyone achieve lasting financial security by delivering innovative solutions that connect, simplify, and transform the industry.


iPipeline is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to gender, race, color, religious creed, national origin, age, sexual orientation, gender identity, physical or mental disability, and/or protected veteran status. We are committed to building a supportive and inclusive environment for all employees.


Responsibilities

As an Expert Business Intelligence Developer at iPipeline, you will play a critical role in the ongoing development, support, and evolution of our enterprise dashboard and reporting solutions, guiding the Data Engineering function. Your work will focus on designing, developing, and maintaining dashboards and reports used internally and externally, while also contributing to our strategic data transformation, migrating to AWS services such as Amazon QuickSight and Redshift to support scalable analytics and AI integration. You will work within a scrum team, participate in sprint planning, backlog refinement, and cross-functional collaboration to deliver data visualisations that drive business value. You will serve as a subject matter expert, mentor, and Security Champion, ensuring best practices across development, deployment, and data governance.



  • Design, develop, and maintain Power BI dashboards and SSRS reports to meet internal and external stakeholder needs.
  • Develop new dashboards and reporting capabilities in AWS using native tools and services.
  • Provide technical leadership on dashboard architecture, data modelling, data visualisation and user experience design.

Agile Development & Team Collaboration

  • Lead estimation and technical input for JIRA stories during sprint planning.
  • Collaborate with scrum team members, Data Analysts, and Data Engineers to deliver high-quality, tested solutions.
  • Ensure all work meets acceptance criteria, is QA-tested, and adheres to established coding standards.

Strategic Projects & Cloud Migration

  • Support and help lead the development of dashboard and reporting solutions in AWS QuickSight, including data source migration to Amazon Redshift.
  • Work with the Data Product Manager to align dashboard development with the company's AI and data strategy.
  • Investigate and assess opportunities to integrate AWS-native services with dashboards.

Performance Optimisation & Data Engineering

  • Optimise complex SQL queries and data pipelines for performance and scalability.
  • Define and maintain ETL processes that feed into dashboards.
  • Collaborate with the Data Engineering team to design scalable data models.

Security & Governance

  • Serve as Security Champion for the dashboard ecosystem, ensuring access control, row-level security, and best practices in secure data design.
  • Participate in security reviews, penetration testing, and governance processes.

Stakeholder Engagement & Communication

  • Liaise with internal teams (e.g. Data Delivery, Sales, IT Support) and external stakeholders to gather requirements, provide training, and support presentations.
  • Lead training programmes and ad-hoc sessions for both internal and external clients on dashboard usage.
  • Represent iPipeline in discussions with external technology partners, such as Microsoft and Amazon.

Leadership & Strategy

  • Define and implement a dashboard development roadmap aligned with strategic objectives.
  • Oversee releases, coordinating resources and timelines.
  • Mentor other Power BI / Dashboard developers and contribute to team knowledge sharing.

Qualifications
Technical Expertise

  • Power BI Desktop:

    • Advanced DAX, Power Query, and star schema modelling
    • Row-level security and access control


  • Power BI Service:

    • Workspace and App management
    • Data Gateway administration
    • Azure Security Group integration


  • SQL (including performance tuning in Redshift or similar columnar stores)
  • Python & R for data manipulation, automation, and analytics
  • Working knowledge of AWS analytics stack (Redshift, QuickSight, Glue, DMS, etc.)
  • Tools: SQL Server Management Studio, ALM Toolkit, Tabular Editor

Development Process

  • Experience working in Agile/Scrum environments
  • JIRA story creation, refinement, and estimation (story points)
  • Full sprint cycle participation (planning, stand-ups, reviews, retrospectives)

Soft Skills & Communication

  • Strong communication skills with both technical and non-technical audiences
  • Stakeholder engagement and training facilitation
  • Self-driven, detail-oriented, and proactive in process improvement

Desirable Experience

  • Demonstrable experience in BI development, with a strong track record of delivering enterprise dashboards, reports and data products and solutions.
  • Proven experience with Power BI and AWS QuickSight, including migration projects.
  • Strong SQL skills and experience optimising complex queries for large datasets in Redshift or similar columnar data warehouses.
  • Background in data engineering, with an understanding of ETL/ELT processes and data modelling.
  • Proficiency in Python and R, particularly for analytics, automation, and data manipulation.
  • Use of source control (GitHub) to manage code repositories through defined branching strategies.
  • Hands-on experience working in Agile/Scrum
  • Strong understanding of data visualisation principles and best practices.
  • Experience implementing data security, row-level access, and secure dashboard sharing.
  • Ability to translate business requirements into technical solutions with minimal guidance.
  • Excellent problem-solving and communication skills.

Desirable Skills

  • Experience integrating dashboards with AI/ML models or predictive analytics.
  • Familiarity with AWS data services (e.g., S3, DBT, Glue, Redshift, Lake Formation).
  • Knowledge of CI/CD practices for BI and analytics tools.
  • Exposure to DevSecOps or formal Security Champion roles within development teams.
  • Certification in Power BI, AWS, or other analytics tools is a plus.
  • Experience in dashboard/data solution migration
  • Involvement in integrating AI/ML outputs into BI dashboards
  • AWS Certifications or equivalent practical experience
  • Familiarity with Microsoft Fabric architecture and upcoming Power BI features

Benefits

We offer a competitive compensation and benefits package, opportunities for career growth, Pension plan with company-matched contributions, generous time off and flexible work/life balance, an employee wellness program, and an awards and recognition program – all in a creative, fast-growing, and innovative company.


Additional

  • Seniority level: Mid-Senior level
  • Employment type: Full-time
  • Job function: Information Technology
  • Industries: Software Development

Referrals increase your chances of interviewing at iPipeline by 2x


Get notified about new Data Engineer jobs in Chelsea? Cheltenham, England, United Kingdom.


We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

Related Jobs

View all jobs

GenAI Data Engineer: Build AI-Powered Data Platform

Data Engineer: Pipelines, Insights & Governance

Senior Data Engineer

Senior Data Engineer

GenAI Data Engineer

Senior Data Engineer

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.