At a Glance
- Tasks: Own and evolve data pipelines, ensuring reliable and scalable analytics solutions.
- Company: Join a forward-thinking company focused on data-driven decision-making.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with opportunities to influence and innovate.
- Why this job: Make a real impact by shaping the future of data engineering in analytics.
- Qualifications: Strong experience in data engineering, SQL, and cloud platforms required.
The predicted salary is between 60000 - 80000 £ per year.
We’re looking for a Senior Data Engineer to take ownership of the data engineering layer that underpins enterprise reporting and analytics. This is a hands‑on role focused on building and running the pipelines, transformations, curated datasets, and quality controls that turn operational data into trusted, usable assets for decision‑making. You’ll play a key role in shaping how data engineering is done within a growing analytics function. In the near term, you’ll strengthen and evolve the platform foundations behind critical analytics use cases. Over time, you’ll help build more reusable, scalable data services that can support a broader range of analytics and digital needs.
Key Responsibilities
- Own and evolve core data pipelines, transformation logic, and curated datasets that support enterprise reporting and analytics.
- Design, build, and maintain scalable data models across warehouse / lakehouse environments, with a focus on reliability, clarity, and reuse.
- Implement strong data quality, validation, monitoring, and operational controls so critical data assets remain trusted and resilient.
- Integrate data from multiple source systems into well‑structured datasets for analytics and reporting use cases.
- Work closely with analytics, BI, platform, and architecture colleagues to ensure downstream reporting and analytics sit on stable engineering foundations.
- Apply strong engineering discipline through CI/CD, version control, documentation, and repeatable delivery patterns.
- Improve performance, maintainability, and scalability of data pipelines and models as the platform grows.
- Help establish reusable patterns and standards for data engineering across the analytics function.
- Support the evolution of the analytics platform so it can serve not only reporting needs today, but broader analytics and digital use cases over time.
Essential Experience / Skills
- Strong senior‑level data engineering experience building and maintaining scalable data platforms and pipelines.
- Strong SQL plus Python / PySpark or equivalent experience for ingestion, transformation, and validation work.
- Experience with cloud data platforms, orchestration tooling, and modern warehouse / lakehouse patterns.
- Experience designing and maintaining curated datasets and data models for analytics use cases.
- Experience implementing data quality, monitoring, validation, and secure / governed data handling.
- Good engineering discipline, including CI/CD, version control, documentation, and repeatable delivery practices.
- Ability to work with technical and non‑technical stakeholders to translate business needs into robust technical solutions.
Desirable Experience / Skills
- Experience with Microsoft Fabric, Azure‑based data engineering, or similar modern cloud data environments.
- Experience supporting analytics or enterprise reporting environments with high expectations around trust, governance, and continuity.
- Familiarity with business‑critical data domains such as finance, operations, or people data.
- Experience helping teams raise engineering maturity through shared standards, patterns, and service ownership.
Why Join / Opportunity
- Take real ownership of important data assets at the heart of enterprise analytics.
- Help shape how data engineering is done within a growing analytics capability.
- Work on meaningful platform foundations that support trusted reporting today and more reusable analytics services over time.
- Influence the move from fragmented data workflows toward more robust, scalable, and well‑governed engineering patterns.
- Partner with a broad set of stakeholders across analytics, BI, platform, and digital teams in a role with clear impact and room to grow.
- Build something lasting: not just pipelines, but a stronger engineering foundation for future analytics delivery.
Senior Data Engineer employer: SLR Consulting Ltd
Join a forward-thinking company that values innovation and collaboration, where as a Senior Data Engineer, you will take ownership of critical data assets that drive enterprise analytics. Our supportive work culture fosters professional growth, offering opportunities to shape the future of data engineering while working alongside diverse teams in a dynamic environment. With a focus on building robust, scalable solutions, you'll play a pivotal role in enhancing our analytics capabilities and making a lasting impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. Attend industry meetups or webinars to meet potential employers and showcase your skills.
✨Tip Number 2
Show off your projects! Create a portfolio that highlights your best work in building data pipelines and models. Share it during interviews or on platforms like GitHub to give hiring managers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL and Python skills. Practice common data engineering problems and be ready to discuss your approach to building scalable data solutions.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you to join our team. Keep an eye on our job listings and make sure your application stands out!
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Senior Data Engineer. Highlight your experience with data pipelines, SQL, and any cloud platforms you've worked with. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our analytics function. We love seeing candidates who can connect their experiences to our mission.
Showcase Your Projects:If you've worked on relevant projects, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build scalable data models and maintain data quality. This helps us visualise your impact.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at SLR Consulting Ltd
✨Know Your Data Engineering Fundamentals
Brush up on your core data engineering concepts, especially around building and maintaining scalable data platforms. Be ready to discuss your experience with SQL, Python, and cloud data platforms, as these will likely come up during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data quality, validation, and monitoring. Highlight any instances where you improved performance or scalability in your previous roles, as this will demonstrate your hands-on experience.
✨Understand the Business Context
Familiarise yourself with the business-critical data domains relevant to the role, such as finance or operations. Being able to translate technical solutions into business value will impress your interviewers and show that you can work with both technical and non-technical stakeholders.
✨Emphasise Collaboration and Communication
Since this role involves working closely with various teams, be prepared to discuss how you've successfully collaborated in the past. Share examples of how you’ve communicated complex technical concepts to non-technical colleagues, as this is key for ensuring stable engineering foundations.
