At a Glance
- Tasks: Design and optimise data structures for business intelligence and analytics.
- Company: Join a forward-thinking company committed to innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Work in a supportive culture that values integrity, collaboration, and enthusiasm.
- Why this job: Make a real impact by connecting data with insights in a dynamic environment.
- Qualifications: Degree in Computer Science or related field; experience in analytics engineering or BI development.
The predicted salary is between 60000 - 80000 £ per year.
The Analytics Engineer plays a key role in connecting the enterprise data platform with business intelligence delivery. Operating within the organisation’s analytical data environment, they design and maintain the structures that make curated, high-quality data available for reporting and insight generation. Working between Data Engineering and the Power BI development team, this role helps build and optimise data warehouses, marts, and modelled tables, ensuring the data layer is efficient, reliable, and accessible. They also lead the development and maintenance of the Enterprise Data Catalogue, providing visibility and governance of structured data assets across the organisation. This is a hands-on technical role, requiring a deep understanding of data modelling, performance optimisation, and modern data engineering practices to enable trusted, scalable, and insight-ready data.
Responsibilities:
- Design, build, and optimise data warehouses, marts, and modelled tables within the enterprise data platform.
- Create curated, analytics-ready data structures to support business intelligence and advanced analytics.
- Collaborate with Data Engineering on pipeline design and data architecture standards.
- Maintain schema documentation, data lineage, and metadata accuracy within the Enterprise Data Catalogue.
- Partner with Power BI Developers and Analysts to translate analytical needs into efficient, governed data structures.
- Align modelling and naming standards across the data platform and BI layers.
- Work with IT, architecture, and governance teams to ensure compliance with security and data management policies.
- Monitor the performance, accessibility, and integrity of the analytical data layer.
- Implement monitoring and validation frameworks to identify and resolve data or performance issues.
- Continuously optimise query performance, refresh cycles, and data architecture.
- Own and maintain the Enterprise Data Catalogue as the authoritative reference for curated data assets.
- Document data lineage, ownership, and certification status to support governance and transparency.
- Contribute to metadata management and data lifecycle processes.
- Recommend and implement modern data practices that enhance scalability, consistency, and automation.
- Support initiatives that prepare the platform for AI and Manufacturing Intelligence integration.
- Stay current with emerging tools, technologies, and approaches in cloud data engineering and analytics.
Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, or related discipline.
- Demonstratable experience in analytics engineering, data engineering, or BI development.
- Proficiency in SQL and experience with data warehousing, schema design, and data modelling.
- Strong understanding of modern cloud-based data platforms and architectures.
Skills:
- Demonstrated problem solving and work prioritisation skills.
- Hands-on experience with Snowflake or an equivalent enterprise data platform.
- Familiarity with modern transformation frameworks (e.g., dbt, Data Factory, or equivalent).
- Experience supporting BI environments such as Power BI, Tableau, or Looker.
- Understanding of metadata management, data governance, and CI/CD principles.
- Exposure to data catalogue or lineage tools.
- Strong collaboration and communication skills, working effectively across technical and business teams.
- Ability to keep up to date with technology and apply it to the business strategic plan.
- Ability to achieve results independently or while working with others.
- Excellent interpersonal and communication skills, with the ability to communicate effectively with end-users, management, and staff.
- Ability to handle multiple priorities involving internal customer requests and demands.
- Ability to excel in a cross-organisational, cross-cultural, global team environment.
- Ability to handle special assignments promptly and professionally.
- Sets a high standard of ethics, professionalism, and competency.
Working Conditions:
Working conditions typical of a climate controlled and professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers.
Safety Requirements:
All employees are required to follow the site EHS procedures and Coherent Scotland EHS standards.
Quality & Environmental Responsibilities:
Depending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System.
Culture Commitment:
Ensure adherence to company’s values (ICARE) in all aspects of your position at Coherent: Integrity – Create an Environment of Trust; Collaboration – Innovate Through the Sharing of Ideas; Accountability – Own the Process and the Outcome; Respect – Recognize the Value in Everyone; Enthusiasm – Find a Sense of Purpose in Work.
Principal Analytics Engineer in Glasgow employer: Coherent
Contact Detail:
Coherent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Analytics Engineer in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Principal Analytics Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects or any cool analytics work you've done. This gives potential employers a taste of what you can bring to the table, and we love seeing creativity in action!
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL and data modelling skills, and be ready to discuss how you’ve optimised data layers in the past. We want to see your problem-solving skills shine through when you talk about real-world scenarios.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who align with our values. Let’s get you that job!
We think you need these skills to ace Principal Analytics Engineer in Glasgow
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in analytics engineering and data modelling. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Show Off Your Technical Skills: Since this role is hands-on, be sure to mention your proficiency in SQL and any experience you have with data warehousing or cloud-based platforms like Snowflake. We love seeing candidates who can demonstrate their technical prowess!
Highlight Collaboration Experience: This position involves working closely with various teams, so share examples of how you've successfully collaborated in the past. Whether it’s with BI developers or data engineers, we want to know how you’ve contributed to team success.
Apply Through Our Website: We encourage you to submit your application through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Coherent
✨Know Your Data Inside Out
Make sure you have a solid understanding of data modelling, performance optimisation, and the specific tools mentioned in the job description, like SQL and Snowflake. Be ready to discuss your past experiences with these technologies and how you've used them to solve real-world problems.
✨Showcase Your Collaboration Skills
This role requires working closely with various teams, including Data Engineering and Power BI developers. Prepare examples of how you've successfully collaborated across teams in the past, focusing on communication and problem-solving skills that led to successful outcomes.
✨Demonstrate Your Governance Knowledge
Familiarise yourself with data governance principles and be prepared to discuss how you've implemented or maintained data catalogues and lineage in previous roles. Highlight your understanding of compliance and security policies, as this is crucial for the position.
✨Stay Current with Trends
The field of analytics engineering is always evolving, so show your enthusiasm for continuous learning. Mention any recent tools or technologies you've explored, especially those related to cloud data engineering and AI integration, to demonstrate your commitment to innovation.