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 career progression.
- Other info: Flexible hours and opportunities for professional development.
- Why this job: Join a fast-paced team and make a real impact on sustainable transport.
- Qualifications: 3+ years in data engineering, strong SQL skills, and experience with cloud platforms.
The predicted salary is between 50000 - 50000 £ per year.
Job type: Permanent
Location: Wrightbus
Closing date: Monday 29 Jun
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.
Data Analytics Engineer 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 and career progression, alongside benefits such as a discretionary bonus, life insurance, and discounts with local businesses. Our culture promotes flexibility and collaboration, making it an ideal place for skilled Data Analytics Engineers to thrive and make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your skills. Use real-life examples from your experience to demonstrate how you’ve tackled challenges in data analytics. Remember, confidence is key!
✨Tip Number 3
Don’t just apply and forget! Follow up on your applications after a week or so. A quick email expressing your continued interest can keep you on their radar and show that you’re genuinely keen on the role.
✨Tip Number 4
Make sure to apply through our website for the best chance of landing that Data Analytics Engineer role. We love seeing candidates who take the initiative to engage directly with us!
We think you need these skills to ace Data Analytics Engineer
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, make sure to mention them! Whether it's building a data pipeline or creating insightful dashboards, we want to know what you've done and how it relates to the role. Visuals can help too!
Apply Early!:Don't wait until the last minute to apply! We encourage early applications as we might close the vacancy if we find the right candidate. Head over to our careers page and get your application in – 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 familiar with the tools mentioned in the job description, like SQL, dbt, and Azure Data Factory. Brush up on your knowledge of how to build and maintain data pipelines, as well as how to optimise performance. Being able to discuss your hands-on experience with these tools will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data quality issues or optimised data processes in the past. Think about specific challenges you faced and how you resolved them. This will demonstrate your analytical thinking and ability to troubleshoot, which are crucial for a Data Analytics Engineer.
✨Understand the Business Context
Research Wrightbus and their focus on zero-emission transport solutions. Be ready to discuss how your role as a Data Analytics Engineer can contribute to their mission. Showing that you understand the business context will help you stand out as a candidate who is not just technically skilled but also aligned with the company’s goals.
✨Prepare Questions for Them
Have a few thoughtful questions ready to ask at the end of your interview. This could be about their data strategy, team dynamics, or how they measure success in this role. Asking insightful questions shows your genuine interest in the position and helps you assess if it’s the right fit for you.
