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Data Leaders Insightsrob Kellaway Former Head Of Data Engineering With Hsbc And Nationwide Building Society

Data leaders’ insights: Rob Kellaway, former head of data engineering with HSBC and Nationwide Building Society

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Data leaders’ insights: Rob Kellaway, former head of data engineering with HSBC and Nationwide Building Society

​Rob boasts a career within technology and data spanning over 20 years and during this time has led data engineering teams on some of the UK’s largest and most complex programmes and transformations during his time with Nationwide, HSBC and Lloyds banking group.

I was lucky enough to sit down with him (virtually, of course) to find out more about his career, the best advice he gives to others, what he looks for when hiring and what excites him most about the future of data.

How did you career start?

I started out working for Thomson Holidays as a graduate entry within their annual milk round intake. Pretty soon I realised that the technical elements of the business interested me more than other aspects, and I moved to work for Lloyds Banking Group as a software developer on a general insurance call centre system. This was when I first encountered data dashboards/reporting and that sparked a life long interest (some would say obsession!), with all things data.

From there I worked for first direct bank, HSBC UK, a 4 year stint in Mexico City for HSBC, and Nationwide Building Society, as well as various ventures and companies in between.

What advice would you give to someone starting out in data engineering?

You have to love it! Seriously - you need to feel the pull of the data - how data can be used for competitive advantage and business value. People often ask me what is the difference between: software engineering, platform engineers, data scientists and data engineers. Obviously, an interest in data is key and how this makes organisations tick, but I would say the data engineers are unique in that they typically provide robust and business facing services to others and want to really help the consumers of the data…it’s a mindset thing.

Keep smiling, be helpful, remember the reason we are here (create value - even if only to keep the NHS funded through these difficult times via the tax revenue we create for the government), and do not let technology be the sole driver.

What is a key lesson you have learnt in your career?

Data is difficult but keep trying! It is one of the hardest disciplines to get right and it is perhaps the one area of tech where business teams, justifiably sometimes, feel that they can do data thing without anyone else’s help. 

In truth, data is all about innovation and that is where business teams can excel, but they also sometimes need help productionising that insight or having reliable and scalable environments to work within, as well as data tooling to help them move more quickly and run value adding services. So, working closely with business teams and using agile approaches, whilst focussing on solving specific and practical business problems brings the best results.

When hiring, what are the key things you look for?

That is a great question. I have just completed an 80+ data hire programme at one of my clients, including a significant chunk of data engineers. I’ll list below the areas I look for:

  1. Genuine interest in data and data engineering technology.

  2. Practical experience of what problems and challenges data engineers can expect to encounter and how to overcome them through a methodological/logical attitude.

  3. Genuine desire to help people and business create value from data  - its no longer much help to just want to build pipelines in the corner of the office, all day long.

  4. Ability to communicate clearly, make compelling points, constructively contribute to a discussion.

  5. Evidence of innovation - be that through improvements, efficiencies and bringing new tech to the table. I want people who are not going to be happy with the status quo, I want people who are continually looking for new and better ways of getting things done.

  6. Persistence and a ''never give up'' attitude - working in data can be tough - we need people who can keep motivated and motive others.

  7. Good quality data engineering skills - use of open source, rather than proprietary.

Note: I am not putting technical skills at the top of my agenda. Of course, these are important, but they are not really a differentiator to me. Good people, motivated people, people who want to work in data can pick up new engineering skills very quickly. 

What are the most interesting innovations you are seeing emerge within data?

Real time analytics via streamed and governed data. In the last 12 months streaming data solutions and the ability to consume streams at scale (safely), but with the ability to fully govern that data, has become an enterprise reality. In today’s businesses most companies are running multiple data platforms, large numbers of data tools (excel), data is governed poorly (despite everyone’s best efforts). Generally, it’s a bit of a mess and more expensive than it needs to be. Moving to a streaming platform, with governance and the ability to secure the data safely for multiple purposes can replace much of the existing provision and run a cheaper price point in the cloud.

DataOps (not DevOps for data) - is now a mission critical requirement for most organisations. Data teams are typically silo’d by function or technology (reporting teams, data engineering teams, data governance teams, modelling teams, consumer teams). This creates many technologies, many handoffs, creates slow and expensive change processs - its often a very gruelling process to anything done and business teams quickly lose trust. DataOps (Agile manifesto, some lean manufacturing, automation and orchestration) provides a new way of innovating with data at the speed of the business - using some of the traditional disciplines needed in data - but organising teams for success along agile themes and being clear on the business value, rather than the technical elements of the solution.