At a Glance
- Tasks: Own and evolve data pipelines, ensuring reliable and scalable analytics solutions.
- Company: Join a forward-thinking company focused on innovative data engineering.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with opportunities to influence and grow your career.
- Why this job: Make a real impact on enterprise analytics and shape the future of data engineering.
- Qualifications: Strong experience in data engineering, SQL, and cloud platforms.
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.
What we’re looking for
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
Join a forward-thinking company that values innovation and collaboration, where as a Senior Data Engineer, you will have the opportunity to take ownership of critical data assets and shape the future of our analytics capabilities. Our supportive work culture fosters professional growth, offering you the chance to influence robust engineering practices while working alongside diverse teams in a dynamic environment. With a focus on meaningful contributions and a commitment to building lasting solutions, this role is perfect for those looking to make a significant impact in the world of data engineering.
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 meetups or webinars related to data analytics and engineering to meet potential employers and learn about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data engineering projects. Include details about the pipelines you've built, the transformations you've implemented, and any data quality measures you've put in place. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with SQL, Python, and cloud data platforms. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We have a range of exciting opportunities waiting for talented individuals like you. Keep an eye on our job listings and make sure to submit your application directly to us for the best chance of landing that dream role.
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! Use it to tell us why you're passionate about data engineering and how you can contribute to our analytics function. Be genuine and let your personality come through.
Showcase Relevant Projects:If you've worked on projects that involved building scalable data models or implementing data quality controls, make sure to mention them. We love seeing real-world examples of your work and how they relate to what we do at StudySmarter.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at SLR Consulting
✨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 in conversation.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data quality, monitoring, and validation. Think about times when you improved the performance or maintainability of data pipelines and be ready to explain your thought process.
✨Understand the Business Context
Familiarise yourself with the business-critical data domains relevant to the role, such as finance or operations. This will help you translate technical solutions into business value during the interview, showing that you can bridge the gap between technical and non-technical stakeholders.
✨Demonstrate Your Collaborative Spirit
Be prepared to discuss how you've worked with cross-functional teams, particularly in analytics and BI. Highlight your ability to communicate effectively with both technical and non-technical colleagues, as this is crucial for the role.
