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For Companies At a Glance
- Tasks: Design and optimise data pipelines to support business initiatives.
- Company: Join Moneypenny, a leading outsourced communications provider with a global team.
- Benefits: Enjoy a hybrid working model and the chance to work with cutting-edge technology.
- Why this job: Be part of a dynamic team delivering impactful data solutions that drive business success.
- Qualifications: 5+ years in data engineering with strong SQL and data warehousing experience required.
- Other info: Opportunity to collaborate across teams and enhance your skills in a fast-paced environment.
The predicted salary is between 36000 - 60000 £ per year.
Moneypenny is a leading provider of outsourced communications, offering high-quality phone answering, live chat, and AI receptionist services. Fast-forward two decades and what started as a single, dedicated PA looking after calls for a handful of local clients, is now a 1000-strong team working across continents from our state-of-the-art UK headquarters in Wrexham, and our US office in Atlanta.
We’re seeking a skilled Data Engineer to support key business initiatives throughout 2025. This contract role is ideal for someone who thrives on designing and optimizing data pipelines from the ground up. Reporting to the Head of Data Engineering, the position offers a hybrid working model with our office based in Wrexham, North Wales. You’ll work across multiple teams, systems, and products—so being self-directed and collaborative is essential. The successful candidate will play a key role in delivering robust, scalable, and maintainable data solutions that empower the business with reliable insights and streamlined processes.
Key responsibilities:
- Develop and maintain scalable data pipelines to support required data integrations for all business areas.
- Design data integration, data quality and support frameworks using re-usable design patterns to reduce the maintenance effort and provide consistent systems.
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements such as automation of manual processes.
- Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
- Collaborate with analytics and business teams to improve data models that feed business intelligence and other analytical tools, increasing data accessibility, and fostering data-driven decision-making across the organisation.
The person:
Essential Experience:
- Experience of working with data warehousing – understanding the techniques to creating highly accurate and high-performing warehousing solutions data warehouse on SQL Server using SSIS with Visual Studio and T-SQL to answer BI requirements.
- Use of API’s to source data.
- A strong SQL expert who can write stored procedures and demonstrate a strong knowledge of the Kimball methodology and cloud-based warehouse design patterns.
- Understanding the importance of data security and associated controls.
- Understanding the GDPR regulations and be fully conversant with the evolving ICO legislation and guidelines.
Preferred Experience:
- Use of the Kingsway component set within SSIS.
- Experience of integrating with SaaS solutions.
- Experience working in a rapidly evolving agile environment.
- 5 + years’ experience in data engineering.
Data Engineer employer: Moneypenny
Contact Detail:
Moneypenny Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as SQL Server, SSIS, and T-SQL. Having hands-on experience or projects that showcase your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Network with current or former employees of Moneypenny on platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during interviews.
✨Tip Number 3
Prepare to discuss your experience with data warehousing and the Kimball methodology in detail. Be ready to share specific examples of how you've designed and optimised data pipelines in previous roles, as this will demonstrate your expertise and problem-solving abilities.
✨Tip Number 4
Stay updated on GDPR regulations and data security best practices. Being knowledgeable about these topics not only shows your commitment to compliance but also highlights your understanding of the importance of data integrity in a business environment.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with SQL Server, SSIS, and T-SQL. Emphasise any projects where you've developed scalable data pipelines or improved data quality.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in the Data Engineer role at Moneypenny. Mention specific skills that align with their requirements, such as your experience with API integration and understanding of GDPR regulations.
Showcase Your Technical Skills: When detailing your experience, focus on your technical skills. Include examples of how you've used SQL to create stored procedures or implemented data security measures in previous roles.
Highlight Collaboration Experience: Since the role requires collaboration across multiple teams, provide examples of past experiences where you worked effectively in a team environment. This could include projects where you collaborated with analytics or business teams to enhance data models.
How to prepare for a job interview at Moneypenny
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL Server, SSIS, and T-SQL in detail. Highlight specific projects where you designed data pipelines or worked on data warehousing solutions, as this will demonstrate your technical expertise.
✨Understand the Business Context
Research Moneypenny and understand their business model and how data engineering supports their operations. Be ready to explain how your role as a Data Engineer can contribute to their goals and improve their data-driven decision-making.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills. Prepare to discuss scenarios where you had to implement process improvements or ensure data quality, showcasing your ability to think critically and work collaboratively.
✨Familiarise Yourself with GDPR and Data Security
Since understanding data security and GDPR regulations is essential for this role, be ready to discuss your knowledge of these topics. Share examples of how you've ensured compliance in previous roles to show your commitment to data integrity.
