Recognition at M&S – Making an Impact from Day One

Starting Strong at Marks & Spencer

Six months into my journey at Marks & Spencer, and I'm already seeing the impact of bringing a customer-first mindset to data engineering. This week, I received recognition from Mark Hoskin, our Senior Data Engineering Manager, during a team meeting that reminded me why I love what I do.

The Recognition

"A big shout out to Vijay from the Data Engineering team. He recently went on his close to customer induction days, but he gave some really great feedback to the business on the things that he identified that could do with improving and what was really nice to see is that you got a really good positive response from the business on it as well and there's been quite an e-mail trail going in on the background about how things can be improved. So really kind of role modelling that close to customer behaviours there Vijay, well done."
— Mark Hoskin, Senior Data Engineering Manager, Marks & Spencer

What This Recognition Means

Being acknowledged for close-to-customer behaviors hits different. It's not just about technical excellence—it's about understanding that every data pipeline, every Streamlit dashboard, and every analytics solution ultimately serves real customers making real purchasing decisions.

The Close-to-Customer Induction Experience

During my induction days, I had the opportunity to:

Shadow customer-facing teams to understand their pain points
Observe how data flows (or doesn't flow) through the business
Identify gaps between what our data platforms provide and what the business actually needs
Engage directly with stakeholders who consume our analytics

What struck me most was the disconnect between technical capability and business usability. We had powerful tools, but the last mile of making data accessible and actionable needed work.

The Feedback That Sparked Change

I didn't hold back. After the induction, I compiled observations and recommendations on:

1. Self-Service Analytics Gaps

Business users were waiting on data teams for simple queries
Opportunity to build Streamlit applications that democratize data access
Need for better documentation and data dictionaries

2. Loyalty Programme Data Accessibility

Customer segmentation data existed but wasn't easily consumable
Real-time metrics were buried in complex dashboards
Opportunity to create business-friendly visualizations

3. Process Improvements

Identified bottlenecks in the data request workflow
Suggested automation opportunities (my old habits die hard!)
Proposed better collaboration patterns between data and business teams

The Response That Made It Worth It

What made this recognition special wasn't just the acknowledgment—it was the business response. Mark mentioned "quite an email trail going on in the background about how things can be improved."

That's the real win. Ideas without execution are just noise, but when the business engages, when people start collaborating on solutions, that's when you know you've made an impact.

Why This Matters

In my 10+ years across Symantec, CEB/Gartner, Optum, Eli Lilly, Channel4, and Sky UK, I've learned that technical brilliance means nothing if it doesn't solve real business problems.

At Sky UK, I built a code generator that made engineers' lives easier.
At Marks & Spencer, I'm focused on making customers' shopping experiences better through data.

That shift in perspective—from engineering efficiency to customer impact—is what excites me about this role.

What's Next

This recognition isn't a finish line; it's validation that the approach is working. Now comes the real work:

Building the solutions I proposed (Streamlit apps for self-service analytics)
Iterating with the business on what actually moves the needle
Demonstrating value through working software, not just slide decks
Continuing to bridge the gap between data engineering and business needs

Lessons for Fellow Data Engineers

If you're joining a new company or team, here's what I learned:

Use your fresh eyes – You'll never have a clearer perspective on inefficiencies than in your first few months
Listen before building – Understand the problem deeply before proposing solutions
Speak the business language – Frame technical improvements in terms of customer or business impact
Follow through – Ideas are cheap; execution is what earns respect
Stay humble – You're there to serve the business and customers, not to show off technical prowess

Gratitude

Thank you, Mark Hoskin, for recognizing not just the feedback but the mindset behind it. And thank you to the M&S business teams who engaged with the ideas and are collaborating on making them reality.

This is what I signed up for—building platforms that empower people and improve customer experiences.

Let's keep building.

P.S. If you're a data engineer struggling to get business buy-in for your ideas, remember: it's not about having the best technical solution. It's about understanding the customer problem so deeply that your solution becomes the obvious next step. Start with "why this matters to customers," and the "how we build it" becomes collaborative, not combative.

Close to customer. Always.

Cheers,
Vijay Anand Pandian