Data Engineer

Verastar Limited
Sale
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

The purpose of the role

To be a subject matter expert responsible for developing and building data engineering pipelines and services to transform / integrate data from operational systems into data analytics and business intelligence (BI) systems.


Responsibilities of the role

  • Work collaboratively with the Data Engineering team, other Data and Insights teams, cross‑functional teams, and business partner teams to deliver data transformation / integration pipelines into data analytics and business intelligence (BI) systems.
  • Maintain, develop, and analyse these data pipelines, seeking always to deliver high availability, simplicity of design, and quality of data.
  • Contribute to the definition and development of data collection, storage and data quality to support a contemporary and responsive reporting and insights architecture in partnership with technology teams and subject matter experts, working to integrate siloed areas of the business.
  • Assist in the development of data quality and governance standards, techniques, and tools, cooperating with technology teams and others to roll these out.
  • Contribute to the development and maintenance of the Business Data Model which documents master and reference data attributes.
  • Endeavour to deliver more than just data by considering how the request can best deliver immediate business value, offering data analysis, profiling and insight where possible.
  • Respond to problems in databases, data processes, data products and services as they occur. Initiate actions monitor services and identify trends to resolve problems and prevent future ones.
  • Build strong, collaborative relationships with key stakeholders across disciplines, being seen as a subject matter expert and trusted advisor.

Success Measures

  • Work quickly and efficiently under tight deadlines through responsive and agile delivery approaches that focus on stakeholder need.
  • Ensure application of effective data governance and security standards that empower and champion a data‑informed culture across the business.
  • Complete work to a high standard, creating solutions that are reliable, flexible and enduring.
  • Pioneering data innovation, to understand the impact of emerging trends on the organisation's data tools, analysis techniques and data usage and building solutions to enable.

Experience

  • Strong technical background and proven ability in data collection, transformation and integration, evidencing understanding of data warehousing and dimensional modelling principles with good understanding of data profiling or analysis.
  • Data modelling. You understand the concepts and principles of data modelling and can produce relevant data models.
  • Practice in working closely with agile teams and stakeholders from discovery to implementation of outcomes, managing stakeholder expectations while seeking continuous improvement in satisfaction and increasing data literacy.
  • Working knowledge of data governance would be very desirable.
  • Testing. You can review requirements, specifications and define test conditions within an agile delivery function and report test activities and results.

The personal capabilities needed to excel in this role

  • Good communication to and between technical and non‑technical stakeholders. Able to facilitate discussions within a multidisciplinary team.
  • Understanding of differing perspectives.
  • Passionate about data, and the insights it brings. Ability to act as a strong advocate for the team.
  • Innovative thinking to deliver business priorities for reporting and insights.

Qualifications and other requirements

  • High degree of competency across the Microsoft SQL stack and working knowledge with Python.
  • Experience in the Microsoft Azure suite advantageous.

In return for your hard work, you’ll get

It takes all kinds of people to make Verastar the success that we are, and we’ve got a range of benefits to make sure everyone is happy.



  • Core benefits including pension contributions and life assurance.
  • Great discounts on 100s of high street and online stores.
  • 25 days holiday rising with service up to 28 days.
  • Your birthday off every year.
  • Option to buy up to 10 extra holidays and sell up to 5 holidays per year.
  • Cycle to work and travel loans for people wanting a greener commute.
  • Wellbeing support including 24/7 access to a GP, mental health support, get‑fit programmes and free legal and financial guidance.

The important extras

  • Hybrid working – option to work three days from home if you choose.
  • Opportunities to get involved in charity fundraising and volunteering days through our giving back movement.
  • Amazing on‑site facilities, such as free on‑site gym, free parking, subsidised café and, to top it off, an on‑site subsidised bar for after‑work drinks, quiz nights and social events.
  • Full‑time / Permanent contract of 37.5 hours per week.
  • No weekends and every bank holiday off.

What happens next

If you’re looking for a new challenge with great benefits at an award‑winning company, then Verastar is the place for you. To be part of our continued success click ‘Apply’ today to take the next step in your career.


Across The Verastar Group, we’re passionate about creating an inclusive team and celebrating our diversity. We want talented people with great skills and matching values to join our teams.


All successful candidates will be subject to pre‑employment checks.



#J-18808-Ljbffr

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.

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.

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.

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.