At a Glance
- Tasks: Design and optimise data platforms for scalable machine learning solutions.
- Company: Join Sainsbury’s, a leader in innovation and technology.
- Benefits: Enjoy flexible working, generous holiday allowance, and exclusive discounts.
- Other info: Collaborative culture with opportunities for continuous learning and career growth.
- Why this job: Make a real impact by shaping data workflows and mentoring future engineers.
- Qualifications: Expertise in PySpark, SQL, and cloud platforms required.
The predicted salary is between 60000 - 80000 £ per year.
About the role
As a Senior Data Engineer, you will play a pivotal role in designing, building and optimising the data platforms, pipelines and services that enable scalable machine learning solutions across the organisation. You will partner closely with Data Scientists to ensure data is reliable, accessible and production‑ready. You will also contribute to engineering excellence by driving best practices, mentoring other engineers, and shaping the technical direction of data and ML workflows across our domain.
Key Responsibilities
- Lead the design and build of high-quality, scalable and reusable data pipelines using Sainsbury’s engineering standards and best practices.
- Integrate and manage data from multiple sources, ensuring consistency, integrity and quality throughout the data lifecycle.
- Provide guidance for the junior & mid Data Engineers on the best practices when building and managing data infrastructure, including data lakes, warehouses, and distributed processing systems (e.g., PySpark, Hadoop).
- Collaborate with data scientists to prepare and transform raw data into formats suitable for machine learning, including feature engineering and data augmentation.
- Implement automation tools and frameworks (CI/CD) to streamline the deployment and monitoring of machine learning models in production.
- Optimise data processing workflows and storage solutions to improve performance and reduce costs.
- Work closely with cross-functional teams, including data science, engineering, and product management, to deliver data solutions that meet business needs.
- Mentorship: junior and mid-level data engineers and provide technical guidance on best practices and emerging technologies in data engineering and machine learning and helping to enhance their skills and career growth.
- Promote a culture of knowledge sharing within the engineering teams by organising regular technical workshops, brown bag sessions, and code reviews.
- Foster a collaborative and inclusive team environment that encourages continuous learning and improvement.
Essential Criteria
- Expertise with PySpark or PyTorch for large-scale distributed data processing, including optimisation, partitioning, and debugging on managed Spark clusters (AWS EMR).
- Experience with containerisation and orchestration tools (e.g., Docker, Airflow, Kubernetes).
- Hands‑on expertise with Snowflake as a cloud data warehouse, including writing and optimising SQL and integrating securely into pipelines.
- Hands‑on experience with cloud platforms (e.g., AWS, GCP, Azure).
- Strong experience with data processing frameworks (e.g., Apache Spark, Flink).
- Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).
- Experience with CI/CD pipelines and automation tools like GitHub Actions.
- Understanding of monitoring and logging tools (e.g., NewRelic, Grafana).
Desirable
- Certifications: AWS Certified Big Data Specialty, Google Professional Data Engineer, or equivalent.
- Strong analytical and problem‑solving skills.
- Excellent communication skills, able to explain complex concepts to non‑technical stakeholders.
- Ability to work independently as well as collaboratively within cross‑functional teams.
What you’ll be doing
- Leadership and Communication: Provide technical direction, set standards, and lead by example in engineering excellence. Facilitate Scrum ceremonies when required (stand‑ups, planning, grooming). Communicate clearly and transparently creating an inclusive environment where diverse opinions are encouraged.
- Collaborative Attitude: Strong team player with a collaborative approach to working with cross‑functional teams within the Media Agency. Open to feedback and willing to provide constructive criticism to others. Be available for the team, responding within a reasonable time frame and if not possible clearly sign post alternative contacts who can guide. Building a community across Media Agency. Contribute to a positive and inclusive atmosphere within the team.
- Knowledge Sharing and Empowerment: Commitment to fostering a learning culture within the team and ensuring knowledge transfer across all levels. Support and mentor C3s and C4s engineers by providing them opportunities to lead initiatives and contribute to the technical roadmap. Share domain expertise proactively and help establish the engineering direction for the team. Support spikes, POCs and early investigative work. Encourage strong developer behaviours (e.g., cameras on for collaboration, documentation, active presence). Lead by example in communication, visibility, accountability and role‑modelling Sainsbury’s values.
What’s in It for You
- Flexible working with a balanced approach to home and office.
- Colleague discounts across Sainsbury’s, Argos and Habitat.
- Private health cover.
- Generous holiday allowance.
- Bonus scheme.
- Pension plan.
- Discounts on gyms, restaurants, holidays, retail and more.
Senior Data Engineer - Nectar (SN) employer: Sainsbury's
At Sainsbury's, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. As a Senior Data Engineer, you will benefit from flexible working arrangements, generous holiday allowances, and extensive colleague discounts across our brands, all while having the opportunity to mentor and grow alongside talented professionals in a supportive environment. Join us to make a meaningful impact in data engineering and machine learning, while enjoying a wealth of employee benefits and career development opportunities.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Nectar (SN)
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work at Sainsbury’s. A friendly chat can sometimes lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best projects, especially those involving PySpark or cloud platforms. This will give you an edge during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your SQL and data processing frameworks. Use mock interviews to build confidence and refine your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the team at Sainsbury’s.
We think you need these skills to ace Senior Data Engineer - Nectar (SN)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with data pipelines, machine learning, and the specific tools mentioned in the job description. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include examples of past projects where you've designed or optimised data platforms. If you've worked with PySpark, Snowflake, or any cloud platforms, let us know! This helps us understand your hands-on experience.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use bullet points for key achievements and make sure your passion for data engineering shines through. We love a good story, but keep it relevant!
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’s super easy!
How to prepare for a job interview at Sainsbury's
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially PySpark, Snowflake, and CI/CD tools. Brush up on your SQL skills and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and other engineers, prepare examples of how you've successfully collaborated in cross-functional teams. Highlight any experiences where you’ve facilitated knowledge sharing or mentored others.
✨Prepare for Problem-Solving Questions
Expect to tackle some technical challenges during the interview. Practice explaining your thought process when solving complex problems, particularly around data processing and optimisation. Use real-world scenarios to demonstrate your analytical skills.
✨Communicate Clearly and Confidently
Strong communication is key, especially when explaining technical concepts to non-technical stakeholders. Practice articulating your ideas clearly and concisely, and don’t hesitate to ask clarifying questions if needed during the interview.