Senior Data Engineer - MS Fabric - Remote - £70k - £75k

Manchester
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - MS Fabric - Remote - £70k - £75k

My client are a leading Data Partner and consultancy looking for an experienced senior data engineer with skills in Microsoft Fabric being the absolute essential here, the Azure Data Platform and Python to join their expanding team in a role which encompasses technical know how and a client-facing skillset.

Salary and Benefits

Competitive salary of up to £75k (DOE)
Annual Performance related bonus of 10%
Remote/hybrid working (once every 2 weeks in office) in Edinburgh, Manchester or London hubs
25 days annual leave (plus bank and public holidays)
Career progress programme - guaranteed learning and development investment
Life insurance
Private medical health insurance
Contributory pension schemeRole and Responsibilities

Possess a wide range of data engineering skills, with a focus on having delivered in Microsoft Azure
Develop good working relationships with clients on a project including interpersonal skills with both business and technical focused colleagues.
Experience working as a data engineer to develop performant end-to-end solutions in a collaborative team environment.
Delivering high-quality pieces of work, proven ability to escalate problems to client / senior team members where necessary and propose possible solutions.
Support building the Consulting practice through contribution to ongoing initiatives. This can include contributing to knowledge-sharing activities, and data services.
Demonstrated success in delivering commercial projects leveraging the above technologies.
Experience overseeing junior staff, including mentoring, reviewing work, and ensuring project alignment with organisational goals and standards.What do I need to apply for the role

Strong in Fabric, Azure Data Factory, Azure Synapse.
Expertise in SQL and Python.
Experience working with relational SQL databases either on premises or in the cloud.
Experience delivering multiple solutions using key techniques such as Governance, Architecture, Data Modelling, ETL / ELT, Data Lakes, Data Warehousing, Master Data, and BI.
A solid understanding of key processes in the engineering delivery cycle including Agile and DevOps, Git, APIs, Containers, Microservices and Data Pipelines.
Experience working with one or more of Spark, Kafka, or Snowflake

My client have very limited interview slots and they are looking to fill this vacancy within the next 2 weeks. I have limited slots for 1st stage interviews next week so if you're interest, get in touch ASAP with a copy of your most up to date CV and email me at or call me on (phone number removed).

Please Note: This is a permanent role for UK residents only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.

Nigel Frank are the go-to recruiter for Power BI and Azure Data Platform roles in the UK, offering more opportunities across the country than any other. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, the London Power BI User Group, Newcastle Power BI User Group and Newcastle Data Platform and Cloud User Group. To find out more and speak confidentially about your job search or hiring needs, please contact me directly at

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.

Careers

How Many Data Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

Jobs

What Hiring Managers Look for First in Data Engineering Job Applications (UK Guide)

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

Education

The Skills Gap in Data Engineering Jobs: What Universities Aren’t Teaching

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.