At a Glance
- Tasks: Lead data strategy and ensure high-quality data delivery across teams.
- Company: Join Sainsbury's, a leader in retail technology transformation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and continuous improvement.
- Why this job: Make a real impact on data-driven decision-making in a dynamic environment.
- Qualifications: Experience in data engineering and strong leadership skills required.
The predicted salary is between 63000 - 77000 £ per year.
The Technology Manager is central to business-critical transformation of technology delivery and achieving Sainsbury's business strategy, working at the heart of a complex matrix operating model spanning internal teams, offshore partners, and strategic technology organisations. Responsible for assuring technology service and delivery provision for Data Engineering, managing the performance of external partners providing engineering and BAU services, and driving financial accountability for the data domain. This role business partners at senior level, ensures fit-for-purpose, secure, efficient data products and applications, and drives continuous improvement in technical processes to deliver value early and often while maximising value for money across contracts and services.
What I am accountable for:
- Data Strategy
- Contribute to data strategies for respective products and functional areas, working closely with Data Architecture, Engineering Teams, and Product Management to ensure alignment with business objectives and data technology principles.
- Partner with Product Managers and Data Science teams to ensure delivery of data engineering services that meet analytical, reporting, and ML requirements, balancing business needs with technical feasibility and operational constraints.
- Ensure data pipelines are delivered in accordance with Sainsbury's Tech guidelines, data governance standards, and technology principles, evolving these based on requirements and learnings from delivery.
- Input into overall data roadmaps, ensuring data solutions fit with business strategy and agenda and that all initiatives have clear and appropriate action plans covering data ingestion, transformation, quality, and access.
- Leadership
- Drive a culture of personal accountability and ownership across direct contributions and external offshore Data Engineering teams, ensuring high performance, data quality standards, and delivery excellence.
- Coach offshore data engineering teams to understand the rationale for technical approaches in data architecture and pipeline design, surfacing and dealing with ambiguity and conflicting demands, escalating appropriately to resolve prioritization conflicts.
- Build collaborative relationships with Data Scientists, Data Analysts, Business Intelligence teams, service providers, suppliers, and wider Sainsbury's Tech colleagues to ensure data services meet required standards and expectations.
Technology Manager - Reporting Platforms in London employer: Retail
As a Home Delivery Driver with Retail, you will be part of a dynamic team that values flexibility and customer satisfaction. Our supportive work culture encourages personal growth through comprehensive training and varied hours, allowing you to balance your professional and personal life effectively. Join us in delivering not just groceries, but also exceptional service across the United Kingdom, while enjoying the unique advantage of working in a role that directly impacts our customers' daily lives.
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We think this is how you could land Technology Manager - Reporting Platforms in London
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We think you need these skills to ace Technology Manager - Reporting Platforms in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Retail, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Retail. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Retail
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
