Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deliver data products for self-service analytics using cutting-edge technologies.
- Company: Join a leading Financial Services organisation driving a major Data Transformation initiative.
- Benefits: Enjoy competitive salary, flexible working arrangements, and opportunities for professional growth.
- Why this job: Be at the forefront of innovation, empowering teams with data-driven insights and solutions.
- Qualifications: Experience in ETL/ELT pipelines, Python, SQL, and data modelling is essential.
- Other info: This is a permanent role with a focus on collaboration and continuous improvement.
The predicted salary is between 36000 - 60000 £ per year.
A leading Financial Services organisation is seeking exceptional Analytics Data Engineers to join their ambitious Data Transformation initiative. This is a permanent role offering competitive compensation and flexible working arrangements.
As an Analytics Data Engineer, you will be at the forefront of their data transformation, designing and delivering data products that empower business teams with self-service analytics capabilities. You'll leverage cutting-edge technologies, including Snowflake, Power BI, Python, and SQL to create scalable, intuitive data solutions that drive business value.
Key Responsibilities- Build Data Products: Collaborate with business domains to design and develop ETL/ELT pipelines and dimensional models optimised for Power BI.
- Drive Governance: Define and enforce data ownership, quality, and security standards within the Data Mesh architecture.
- Enable Self-Service: Create intuitive data models and provide training to empower business users to explore data independently.
- Own the Data Lifecycle: Take end-to-end responsibility for data products, from conception to deployment and continuous improvement.
- Champion Innovation: Stay current with the latest trends and advocate for best practices across the organisation.
We're looking for a curious, organised, and outcome-driven professional with a passion for data and collaboration. You should bring:
- Technical Expertise: Proven experience coding ETL/ELT pipelines with Python, SQL, or ETL tools, and proficiency in Power BI, Tableau, or Qlik.
- Data Modelling Skills: Strong knowledge of dimensional modelling and database principles.
- Governance Experience: Track record of working in democratized data environments, establishing controls and guardrails.
- Collaboration & Communication: Ability to work effectively with senior stakeholders, present data solutions, and guide business users.
- Problem-Solving Mindset: Exceptional analytical skills to tackle complex data challenges and deliver reliable, high-performance code.
If you are open to exploring this role further, please respond to this advert with your latest CV for review.
Analytics Data Engineer employer: McCabe & Barton
Contact Detail:
McCabe & Barton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Data Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Snowflake, Power BI, Python, and SQL. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the financial services sector, especially those working in data roles. Attend industry meetups or webinars to connect with potential colleagues and learn more about the company culture at StudySmarter.
✨Tip Number 3
Prepare to discuss your experience with data governance and how you've implemented quality and security standards in previous roles. Be ready to provide examples of how you've successfully collaborated with business teams to deliver data solutions.
✨Tip Number 4
Showcase your problem-solving mindset by preparing to discuss specific challenges you've faced in data engineering. Think of scenarios where you had to innovate or improve existing processes, as this aligns well with the role's emphasis on championing innovation.
We think you need these skills to ace Analytics Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with ETL/ELT pipelines, Python, SQL, and Power BI. Use specific examples to demonstrate your technical expertise and problem-solving skills.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data and collaboration. Mention how your background aligns with the responsibilities of the Analytics Data Engineer role and express your enthusiasm for contributing to the company's data transformation initiative.
Highlight Governance Experience: If you have experience in data governance or working in democratized data environments, be sure to include this in your application. Explain how you've established controls and standards in previous roles to ensure data quality and security.
Showcase Collaboration Skills: Emphasise your ability to work with senior stakeholders and guide business users. Provide examples of how you've effectively communicated data solutions and empowered others to explore data independently.
How to prepare for a job interview at McCabe & Barton
✨Showcase Your Technical Skills
Be prepared to discuss your experience with ETL/ELT pipelines, Python, SQL, and Power BI. Bring examples of projects where you've successfully implemented these technologies, as this will demonstrate your technical expertise.
✨Understand the Business Context
Research the financial services industry and the specific company you're interviewing with. Understanding their data transformation goals will help you tailor your responses and show that you're genuinely interested in contributing to their success.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical skills and problem-solving mindset. Be ready to walk through how you would tackle complex data challenges, perhaps by discussing a past experience where you overcame a significant obstacle.
✨Demonstrate Collaboration Skills
Since the role involves working with senior stakeholders and guiding business users, be prepared to share examples of how you've effectively communicated and collaborated in previous roles. Highlight any training or mentoring experiences you've had.
