Job Description

About the role

SDM - Data Science Engineering


We are seeking a

Software Development Manager (SDM)

to lead our

Data Science

Engineering teams

at Tesco. These teams work closely with Commodity and Forecasting Data

Scientists to develop and scale solutions that forecast the prices of commodities Tesco

purchases globally -- a system with significant, real-world business impact.

This is not a generic engineering management role. You will set the

technical direction for Data

Science Engineering

, shaping the roadmap to take advanced scientific models from prototype

to production, building resilient platforms, and scaling solutions to handle massive data volumes

and operational complexity.

The role requires both a high technical and leadership bar: you will define and execute technical

strategy, make principled engineering trade-offs, and grow a world-class team that delivers

robust, production-grade data science solutions.

You will be responsible for

Responsibilities

Lead technical strategy

: Define and drive the technical vision for Data Science

Engineering, ensuring solutions scale reliably into production.

Build and engage teams

: Hire, retain, and grow talented engineers, fostering a culture

of inclusion, excellence, and collaboration.

Shape the roadmap

: Lead planning for Data Science Engineering, ensuring clear

purpose and direction while prioritising work that drives measurable value.

Enable delivery

: Partner with Data Scientists, Engineers, and Product Managers across

the software lifecycle to design, build, and deploy high-quality, resilient systems.

Deliver robust solutions

: Ensure your teams produce production-ready code, scalable

pipelines, and resilient platforms that operationalise scientific models.

Support operations

: Establish processes to support production systems, resolve

incidents, and perform root-cause analysis.

Raise the bar

: Drive strong engineering practices, applying modern SDLC principles

(Agile/Scrum/Kanban) to release robust, maintainable software.

Advance architecture

: Lead group discussions on system design and architecture,

balancing long-term scalability with delivery needs.

Contribute to planning

: Input into budget planning and forecasting for the Data Science

domain.

Drive improvement

: Continuously evolve technology, infrastructure, processes, and

practices to increase system reliability and team velocity.

Share and mentor

: Mentor engineers, develop leaders, and share knowledge with the

wider engineering and data science communities.

Stay ahead

: Explore emerging areas such as Generative AI, LLMs, and MLOps

practices, guiding their responsible adoption into production contexts.



Ideal Candidate Pro?le

You bring a strong background in

Engineering or Data Science

, with deep experience in the

data science toolkit (programming, ML, MLOps, etc.)

and a proven record of taking scientific

solutions into production at scale.

You will need

Must-haves

Experience building and leading high-performing engineering teams. Advanced degree in Engineering, Computer Science, Mathematics, or a related field. Demonstrable experience building

scalable and resilient systems

in data-heavy

environments.

Strong programming experience, with fluency in Python and familiarity with multiple

languages.

Solid understanding of common data structures, algorithms, and software design

principles.

Hands-on experience with DevOps tooling (Terraform, Ansible) and CI/CD practices. Proficiency with Git and modern software lifecycle tooling. Experience deploying and running solutions in the cloud (preferably Azure). Familiarity with Agile methodologies (Scrum, Kanban). Ability to make

well-reasoned, technically grounded decisions

that balance scalability,

constraints, and business impact.

Nice-to-haves

Experience with open-source Data Science environments and libraries. Awareness of emerging

MLOps practices

. Knowledge of big-data technologies such as Apache Spark. Proven experience building and deploying ML systems beyond prototyping. Understanding of LLMs, Generative AI, and emerging AI engineering design patterns and

challenges.

Values

Active learner

: Stay curious and current with evolving tools and technologies.

Technical excellence

: Maintain a high bar for software quality, scalability, and resilience.

Leadership impact

: Positively influence the teams you lead and the people you

manage, creating clarity of vision and purpose.

Practical and impact-oriented

: Focus on building systems that work reliably and deliver

real-world business value.

Collaborative and thoughtful

: Navigate technical trade-offs and system design

decisions with empathy, clarity, and rigour.

Team

At Tesco, our Data Science team builds scalable solutions to complex business challenges across

stores, online, supply chain, marketing and Clubcard. We apply advanced machine learning,

generative AI, and large language models (LLMs) to personalise customer experiences, optimise

operations and drive innovation. We work across several business domains, including customer

experience, online, fulfilment, distribution, commodities, store operations and technology. Team

members rotate across domains to broaden their expertise and impact.

We foster a culture of continuous learning, dedicating 10% of the working week to personal

development. Our team benefits from academic partnerships, regular knowledge-sharing events

and a collaborative, inclusive environment that values work-life balance and professional growth.

Whats in it for you?

At Tesco, we are committed to providing the best for you.

As a result, our colleagues enjoy a unique, differentiated, market- competitive reward package, based on the current industry practices, for all the work they put into serving our customers, communities and planet a little better every day.

Our Tesco Rewards framework consists of pillars - Fixed Pay, Incentives, and Benefits.

Total Rewards offered at Tesco is determined by four principles -simple, fair, competitive, and sustainable.

Salary

- Your fixed pay is the guaranteed pay as per your contract of employment.

Leave & Time-off

- Colleagues are entitled to 30 days of leave (18 days of Earned Leave, 12 days of Casual/Sick Leave) and 10 national and festival holidays, as per the company's policy.

Making Retirement Tension-FreeSalary

- In addition to Statutory retirement beneets, Tesco enables colleagues to participate in voluntary programmes like NPS and VPF.

Health is Wealth

- Tesco promotes programmes that support a culture of health and wellness including insurance for colleagues and their family. Our medical insurance provides coverage for dependents including parents or in-laws.

Mental Wellbeing

- We offer mental health support through self-help tools, community groups, ally networks, face-to-face counselling, and more for both colleagues and dependents.

Financial Wellbeing

- Through our financial literacy partner, we offer one-to-one financial coaching at discounted rates, as well as salary advances on earned wages upon request.

Save As You Earn (SAYE)

- Our SAYE programme allows colleagues to transition from being employees to Tesco shareholders through a structured 3-year savings plan.

Physical Wellbeing

- Our green campus promotes physical wellbeing with facilities that include a cricket pitch, football field, badminton and volleyball courts, along with indoor games, encouraging a healthier lifestyle.

About Us

Tesco in Bengaluru is a multi-disciplinary team serving our customers, communities, and planet a little better every day across markets. Our goal is to create a sustainable competitive advantage for Tesco by standardising processes, delivering cost savings, enabling agility through technological solutions, and empowering our colleagues to do even more for our customers. With cross-functional expertise, a wide network of teams, and strong governance, we reduce complexity, thereby offering high-quality services for our customers.

Tesco in Bengaluru, established in 2004 to enable standardisation and build centralised capabilities and competencies, makes the experience better for our millions of customers worldwide and simpler for over 3,30,000 colleagues

Tesco Technology

Today, our Technology team consists of over 5,000 experts spread across the UK, Poland, Hungary, the Czech Republic, and India. In India, our Technology division includes teams dedicated to Engineering, Product, Programme, Service Desk and Operations, Systems Engineering, Security & Capability, Data Science, and other roles.

At Tesco, our retail platform comprises a wide array of capabilities, value propositions, and products, essential for crafting exceptional retail experiences for our customers and colleagues across all channels and markets. This platform encompasses all aspects of our operations - from identifying and authenticating customers, managing products, pricing, promoting, enabling customers to discover products, facilitating payment, and ensuring delivery. By developing a comprehensive Retail Platform, we ensure that as customer touchpoints and devices evolve, we can consistently deliver seamless experiences. This adaptability allows us to respond flexibly without the need to overhaul our technology, thanks to the creation of capabilities we have built.