Torq Pagdin is the Director of Data Engineering at Expedia, where he leads a world-class team of 90 engineers and developers based across multiple territories; UK, Eastern Europe, and India.

The Key Behind Thriving Fintech

Torq Pagdin is the Director of Data Engineering at Expedia, where he leads a world-class team of 90 engineers and developers based across multiple territories; UK, Eastern Europe, and India. Torq is responsible for devising the group vision and strategy for the data engineering and data platform teams.

 

Career path

A career in technology seemed unlikely when Torq was in education as his passion (and degree subject) lied within Maths & Astrophysics. Despite an academic career seeming most probable, Torq always saw himself first and foremost as a problem-solver and soon realised that a career in technology would present him with the opportunity to satisfy the desire to solve real world problems.

Like many aspiring technologists at the time, it was IBM who presented him with his first step in to the world of tech and it was here that he developed a more specific passion for data; seeing a synergy between data and physics as both were describing and illustrating a real world action. After 15 years and numerous roles, Torq moved on to assume responsibility for the BI support team at Sky; this where he and his team were charged with ensuring the quality of data and applications, thus becoming the de facto ‘gateway to production’.

After building a high performing and ultimately self-sufficient team at Sky, Torq was presented with the opportunity to join Expedia, where he felt he could make a real difference. On day one he took over a team of 15, which now, just four years later, sits at 95 across data engineering and data platforms.

 

What are some of the key lessons you’ve learnt in your career?

Don’t stop moving

Torq has learnt a number of key lessons during his career, one of the earliest was learnt at IBM, where he realised that you must not stop moving, particularly when pursuing a career in technology. Despite being at IBM for over 15 years, Torq held a number of positions, learning the value of keeping the next career step in mind. He learnt it was important to ensure that you are always enhancing and developing skills that will maximise the opportunity to get the next role that you desire.

 

Collaborate

After working at a software company for such a long time, Torq was interested in finding out how businesses that weren’t software companies by trade were utilising technology. After joining Sky, he found that despite their high investment in tech, they understandably did not have the same level of access to tech that IBM did. In this instance he realised that collaboration takes on a whole new dimension of importance and the culture of a company is vitally important to success, happiness and wellbeing.

 

Share your successes

One of the biggest challenges that face technologists is how they demonstrate and express the value they can bring. Torq has seen on many occasions that exceptional levels of work can often go unrecognised within businesses, not just because of a lack of understanding of tech by the business, but often because people are reluctant to vocalise and share their successes.

 

What would be your advice to data engineers at an earlier stage of their career?

Add more strings to your bow

What Torq sees an awful lot of is Data Engineers focusing their attention in a certain technical area – whether that be a specific programming language or platform. Whilst being a subject matter expert has value, all indicators suggest we are heading to a world where ‘multi-cloud’ is the norm and as a result, Data Engineers need to have as many strings to their bow as possible. This is not only so you possess a wider knowledge base, but also because the specific area you may be an expert within may not always be the best solution to solve the wider problem.

 

Always keep learning

Similarly, to the above, a key piece of advice is to keep learning, even if it might not feel as though it immediately helps you in your current role. Having a deeper understanding of the tech that is used elsewhere in the business will help you to ensure you’re adding as much value as possible. It will also help broaden your future options when the time comes to move into your next role, as mentioned earlier, don’t stop moving!

 

Vocalise your wins

As mentioned earlier, Torq strongly advises you don’t assume that everybody recognises and sees all the good work you do. It’s important to ensure you are sharing your wins.

 

What do you look for when hiring data engineers?

A problem-solving mindset

As alluded to earlier, being a problem solver is an essential skill to having a successful career in any field, but particularly within technology. As a result, having a ‘problem-solving mindset’ is something Torq always wants to see when hiring. There are several ways Torq goes about assessing this; one of which could be by asking prospective candidates to explain or describe instances where they have identified a personal skills gap and how they have tried to plug that gap.

 

Passion & enthusiasm

A passion and enthusiasm for technology seems an obvious thing to look for but is undoubtedly essential. Most of this can be ascertained during an interview, not so much in language used but in paralinguistic features such as tempo, intonation, pitch and pace of speech.

 

Multiple strings to the bow

As mentioned earlier, hiring the right person is a rarely a case of finding a square peg for a square hole. When hiring, Torq looks not only for people who can fill their primary role, but also people that have a secondary layer of value they can add to the team although it may not be a core part of their job from day one.

 

Diversity – background and cognition 

Particularly when working at Sky, Torq saw first-hand the value that diverse teams had, for a multitude of reasons. Building ‘diverse’ teams can be a very tricky task, particularly considering the undeniable gender and ethnicity skills gap we face in the world of tech. Torq believes that in order to redress this gender & ethnicity imbalance, companies must be more flexible in their recruitment and interview process, as well as being more compromising when it comes to expected competency levels before joining. If companies are serious about diversity, they must be willing to accept a responsibility to upskill candidates themselves.

Diversity of course doesn’t just refer to gender or ethnicity. Teams should also have diversity when it comes to ways of thinking and educational background, thus bringing a new array of approaches when it comes to solving problems. Again, Torq believes that being flexible in hiring and interview processes is important if companies are going to provide this talent with a genuine opportunity.

 

What innovations most interest you in the world of data?

Data reliability engineering

There is no question that there are infinite possibilities when it comes to the future of data and technology and it’s often the cause of heated debate. Machine learning is one thing that most agree will be adopted far more widely; the success of which of course, will rely heavily on quality of data. Torq recently wrote an article around Data Reliability Engineering, whereby teams of developers that specialise in data pipelines are charged with ensuring quality of the data and in turn fixing any issues needed.

 

Multi Cloud Accessibility

As mentioned earlier, we are moving more and more towards a multi cloud world where companies and developers are utilizing different platforms. Torq believes that a job optimizer would work in a way whereby developers build code without having prior knowledge of where it will be processed. A job optimizer would then decide how and where the most efficient and cost-effective method would be. This process, whilst labour intensive initially, would result in higher quality at a lower cost.  

 

Speed layer solutions

Another innovation that Torq envisages becoming a mainstay in the not too distant future is speed layer solutions such as Dremio, OmniSci or Starburst which allows Data Science and Analytics teams to access their data quicker than ever before.