At a Glance
- Tasks: Design and optimise data platforms for scalable machine learning solutions.
- Company: Join Sainsbury’s, a leader in innovative data engineering.
- Benefits: Enjoy flexible working, private health cover, and generous 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.
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 optimizing 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
- 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 signposting 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) in London employer: Sainsbury's
Sainsbury's is an exceptional employer that prioritises a collaborative and inclusive work culture, offering flexible working arrangements that promote a healthy work-life balance. As a Senior Data Engineer, you will benefit from extensive mentorship opportunities, access to cutting-edge technologies, and a commitment to continuous learning, all while enjoying generous employee perks such as discounts across Sainsbury’s brands and private health cover.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Nectar (SN) in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Sainsbury’s or in similar roles on LinkedIn. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Be ready to discuss your experience with PySpark, SQL, and cloud platforms. We want to see how you can apply your knowledge to real-world problems!
✨Tip Number 3
Show off your collaborative spirit! During interviews, highlight examples of how you've worked with cross-functional teams. We love seeing candidates who can communicate complex ideas clearly and foster teamwork.
✨Tip Number 4
Don’t forget to follow up after your interview! A quick thank-you email can keep you top of mind and show your enthusiasm for the role. Plus, it’s a great chance to reiterate why you’re a perfect fit for the team.
We think you need these skills to ace Senior Data Engineer - Nectar (SN) in London
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 is your chance to shine.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your technical expertise and how you can contribute to our team. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows you're keen on joining us at StudySmarter!
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 cross-functional teams, prepare examples that highlight your collaborative experiences. Think of times when you’ve successfully communicated complex data concepts to non-technical stakeholders.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical and problem-solving abilities. Be ready to walk through your thought process on optimising data pipelines or troubleshooting issues in a distributed processing environment.
✨Demonstrate Leadership and Mentorship
As a Senior Data Engineer, you’ll be expected to mentor junior engineers. Prepare to discuss your approach to leadership, including any past experiences where you’ve guided others or contributed to a learning culture within your team.