At a Glance
- Tasks: Design and build data pipelines using Azure technologies to power analytics and reporting.
- Company: A growing organisation focused on innovative data solutions.
- Benefits: Competitive salary, hybrid work, generous holidays, and a shares scheme.
- Other info: Exciting career growth opportunities in a modern cloud environment.
- Why this job: Join a dynamic team and shape the future of data engineering with cutting-edge tools.
- Qualifications: Experience in data engineering, Azure Data Factory, and strong Python or SQL skills.
The predicted salary is between 50000 - 57000 £ per year.
A growing organisation is seeking a skilled and motivated Data Engineer to join its data platform team and help build the next generation of its Azure and Microsoft Fabric‑based data estate. This role is ideal for an engineer who enjoys designing robust pipelines, shaping modern data layers, and working closely with analysts, architects, and business stakeholders to deliver high‑quality, governed data products. If you want to work with cutting‑edge Azure technologies, contribute to a modern medallion‑based architecture, and play a key role in developing scalable, reliable data solutions, this is an excellent opportunity.
The Opportunity
You will design, build, and operate data pipelines and platform components that power analytics, reporting, and operational systems across the organisation. Working within a modern cloud environment centred on Microsoft Fabric, you will help evolve the data platform, improve data quality, and support the delivery of trusted, well‑structured data products.
- Basic salary £50-57k
- A discretionary bonus scheme based on company and personal performance (defined each year, usually around 5%)
- A hybrid work arrangement – 3 days a week in Manchester office
- A pension scheme of 5% matched contribution
- Company shares scheme – once a year you can buy shares at a discounted rate and pay for these monthly over 3 years before cashing them in or getting your saved money back.
- Life Assurance x4 salary
- 33 days holidays (including bank holidays)
- EAP Benefits portal providing discounts to many leading brands
Data Pipeline and Platform Engineering
- Design, build, and maintain scalable ELT/ETL pipelines using Azure Data Factory and Microsoft Fabric.
- Implement and maintain medallion architecture (Bronze, Silver, Gold) across the data platform.
- Engineer reliable ingestion from APIs, databases, flat files, and event streams.
- Monitor pipeline performance, troubleshoot failures, and implement observability and alerting practices.
Master Data and Data Quality
- Support the design and operation of master data management frameworks.
- Apply data quality rules, validation logic, and deduplication processes.
- Work with business teams to define canonical entities, hierarchies, and golden records.
Azure and Cloud Platform Engineering
- Work hands‑on with Azure services including ADLS, Azure SQL, ADF, and Event Hubs.
- Manage storage layers including Delta Lake and OneLake within Microsoft Fabric.
- Contribute to infrastructure‑as‑code practices and environment provisioning.
Integrations and APIs
- Design and maintain integration patterns across internal systems and third‑party platforms.
- Build and consume REST APIs and event‑driven integrations to support near real‑time data flows.
- Collaborate with software engineers and architects to ensure secure, scalable integrations.
Required Skills and Experience
- Solid hands‑on experience in data engineering, including pipelines, ETL/ELT, and data modelling.
- Proficiency with Azure Data Factory for orchestration and data movement.
- Experience with or strong interest in Microsoft Fabric and its lakehouse and pipeline capabilities.
- Practical understanding of medallion architecture and structured data layers.
- Familiarity with master data management concepts.
- Strong skills in Python and/or SQL for transformation, automation, and quality checks.
- Experience integrating with APIs and designing robust data integration patterns.
- Good understanding of Azure services including ADLS, Azure SQL, Key Vault, and Event Hubs.
- Experience with Fabric Lakehouses, Warehouses, and Data Pipelines.
- Exposure to streaming or event‑driven patterns such as Event Hubs or Kafka.
- Familiarity with DevOps, CI/CD, Git, and Azure DevOps.
- Knowledge of data governance, cataloguing, or Microsoft Purview.
- Background in high‑volume operational or analytical environments.
Data Engineer employer: Insight Talent Partners
Join a forward-thinking organisation as a Data Engineer, where you'll be at the forefront of building innovative data solutions using cutting-edge Azure technologies. With a hybrid work model based in Manchester, you will enjoy a supportive work culture that prioritises employee growth through opportunities for skill development and collaboration with talented professionals. Benefit from a competitive salary, generous holiday allowance, and unique perks like a company shares scheme, ensuring your contributions are recognised and rewarded.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving Azure and Microsoft Fabric. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when designing pipelines or working with APIs, as this will demonstrate your expertise and problem-solving skills.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Azure, data pipelines, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Be sure to mention your familiarity with Microsoft Fabric and medallion architecture.
Showcase Your Technical Skills:Don’t forget to showcase your technical skills in Python, SQL, and Azure services. We love seeing practical examples of how you've used these technologies in your previous roles or projects.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Insight Talent Partners
✨Know Your Tech Stack
Make sure you’re well-versed in Azure Data Factory, Microsoft Fabric, and the medallion architecture. Brush up on your knowledge of ELT/ETL processes and be ready to discuss how you've implemented these in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data engineering. Think about times when you had to troubleshoot pipeline failures or improve data quality, and be ready to explain your thought process.
✨Understand the Business Context
Familiarise yourself with how data engineering supports business goals. Be prepared to discuss how your work can impact analytics and reporting, and how you can collaborate with analysts and stakeholders to deliver high-quality data products.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy, team dynamics, and future projects. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.