At a Glance
- Tasks: Build and maintain data pipelines, transforming data into actionable insights.
- Company: Wrightbus, a leader in zero-emission transport solutions.
- Benefits: Discretionary bonus, life insurance, discounts, free parking, and flexitime.
- Other info: Great career progression and professional development opportunities.
- Why this job: Join a fast-paced team and make a real impact on sustainable transport.
- Qualifications: Degree in a related field and 3 years of data engineering experience.
The predicted salary is between 45000 - 55000 £ per year.
Location: Wrightbus
Closing date: Monday 29 Jun 2026 08:00
All applicants must hold valid right to work in the UK. Please be aware that we are unable to provide visa sponsorship for this position now or in the future.
Wrightbus is a fast-paced, high-growth company at the forefront of zero-emission transport solutions. We're looking for skilled and motivated Data Analytics Engineer who owns how data moves across the business.
The Role:
- Build and maintain pipelines that bring data together from across the business (SQL databases, REST APIs, SaaS applications, flat files and event streams) into a central platform such as Microsoft Fabric/Snowflake.
- Develop ELT/ETL processes using tools such as dbt, Power Query (M), Spark, Azure Data Factory or Fabric Data Pipelines and Dataflows Gen2.
- Design dimensional models and reusable semantic models that capture business logic once and serve it consistently to every downstream tool.
- Author efficient transformations in SQL, dbt or DAX for metrics such as year-on-year change, rolling averages and cohort analysis.
- Keep models lean and performant; sound modelling typically reduces query latency by 30-60% and prevents inconsistent or incorrect KPIs.
- Profile, validate and cleanse incoming data, and build automated tests and data-quality checks so issues are caught before they reach a report.
- Monitor pipeline and refresh runs, troubleshoot failures, and meet agreed SLAs (for example, refresh windows under 30 minutes).
- Tune platform performance and cost using partitioning, aggregations, query optimisation and appropriate storage/compute choices.
- Manage deployment across environments, configure row-level and object-level security, and support CI/CD and DataOps pipelines for releases and rollback.
- Build and certify trusted datasets and semantic models so business users can safely explore data and build their own reports across whichever tools suit them (Power BI, Fabric, Excel or others).
- Deliver reference dashboards and reports in the most appropriate tool for the audience, treating the visualisation layer as interchangeable on top of a solid data foundation.
- Produce clear, well-laid-out visuals that reduce decision lag and help teams act quickly.
- Run regular (weekly or biweekly) sessions with product owners and business stakeholders to translate business questions into measurable KPIs, data requirements and prototypes.
Requirements:
- A third-level qualification in Computer Science, Information Systems, Data, Software Engineering or a related discipline is preferred.
- Proven experience (typically 3 years) in data, analytics or BI roles, with a strong recent focus on data engineering and modelling rather than a single reporting tool.
- Experience building data pipelines and models that integrate three or more major data sources.
- Experience working with large datasets, for example exceeding 50 million rows.
- Hands-on delivery on at least one modern cloud data platform such as Microsoft Fabric, Snowflake, Databricks, Synapse or BigQuery.
- Experience building governed self-service and semantic layers that enable other teams to report independently.
The Benefits:
- Discretionary bonus
- Life Insurance
- Medicash scheme
- Discount with local businesses e.g. Galgorm Spa Resort and McAtamney's.
- Free car parking
- Canteen
- Career progression
- Professional development
- Flexitime
To be considered for this role you will be redirected to and must complete the application process on our careers page. To start the process click the Continue to Application or Login/Register to apply button below.
Data Analytics Engineer in Ballymena employer: Wrightbus
Wrightbus is an exceptional employer, offering a dynamic work environment at the forefront of zero-emission transport solutions. With a strong focus on employee growth, we provide opportunities for professional development, flexible working hours, and a range of benefits including a discretionary bonus and discounts with local businesses. Join us in a culture that values innovation and collaboration, where your contributions directly impact the future of sustainable transport.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analytics Engineer in Ballymena
✨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 projects, pipelines, and any cool visualisations you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and practical tasks. Practice explaining your thought process and how you tackle problems, as this will help you shine during technical interviews.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, early applications are encouraged, so get your name in there before the competition heats up!
We think you need these skills to ace Data Analytics Engineer in Ballymena
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Analytics Engineer role. Highlight your experience with data pipelines, SQL, and any relevant tools like dbt or Azure Data Factory. 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 mission at Wrightbus. Keep it concise but impactful – we love a good story!
Showcase Your Projects:If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build and maintain data pipelines. We’re keen to see your hands-on experience in action.
Apply Early!:Remember, we might close the vacancy early if we get enough applications. So, don’t wait until the last minute! Head over to our careers page and get your application in as soon as you can. We can't wait to hear from you!
How to prepare for a job interview at Wrightbus
✨Know Your Data Tools
Make sure you’re well-versed in the tools mentioned in the job description, like SQL, dbt, and Azure Data Factory. Brush up on your knowledge of data pipelines and how to optimise them, as this will likely come up during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles related to data engineering. Think about how you’ve troubleshot pipeline failures or improved query performance, and be ready to share those examples.
✨Understand the Business Impact
Wrightbus is focused on zero-emission transport solutions, so it’s crucial to understand how your role as a Data Analytics Engineer can contribute to their mission. Be prepared to discuss how data-driven decisions can impact sustainability and efficiency.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current data projects or how they measure success in their data initiatives. This shows you’re engaged and thinking ahead.
