Being a data engineer with a consulting company is extremely rewarding. The nature of consulting gives data engineers the ability to work on vastly different projects, to collaborate with clients within diverse industries and to solve high-impact problems.
As a data engineering consultant, every several months you’ll be part of a new multi-disciplinary team of engineers, data scientists, strategic consultants, designers and more. In my case, my contribution to the team typically revolves around building advanced analytics solutions, implementing large-scale data pipelines and creating new digital businesses with clients.
Sharpening my skills
Over the past two and a half years with McKinsey, my growth has skyrocketed–both in my engineering and consulting skills. As a consultant, McKinsey's hands-on training and feedback culture reinforced and strengthened my leadership, communication, and management skills.
As an engineer, I’m learning new technologies, whether open-source like PySpark, Kedro, NodeJS and GraphQL or enterprise like Databricks, CDSW and NiFi. Being coached and mentored by senior technical colleagues pushes me to further sharpen my technical skills.
For example, on a study in Bangkok, my team was building two mobile applications using React Native, NodeJS and GraphQL. Being relatively new to building software with a Javascript tech stack, I was new to some of the best practices of Javascript, like handling loose typing or best practices around asynchronous programming.
After discussing that this was one my learning objectives, a senior developer who was well-versed in Javascript supported me in on-the-job training (e.g. pair programming and joint code reviews) and continuously sent me resources like Hackernoon articles and tech conference videos to study very specific topics.
An exhilarating experience
In my time as a McKinsey data engineer, one of my most exhilarating experiences was working on a mine in rural Indonesia. I was completely new to mining, with no knowledge of how a mine works or what one really looked like. I remember bringing along stacks of research papers and documents on mining. I felt thoroughly overwhelmed, but knew this would be an opportunity of a lifetime that I would never get outside of McKinsey.
It took one international, one domestic, and one twin-propeller flight to reach the small local airport of this rural, beautiful mining town. As I prepared to enter the mine site, I put on my high-visibility vest, metal-toe mining boots, helmet and protective goggles. Wearing what felt like five kilograms of protective gear, feeling the fresh air, and looking around the vast site was a truly surreal moment for me.
On this five-week project, my team and I used advanced analytics and machine learning to help optimize the throughput of the client’s mineral production. We built proof-of-concept Kedro pipelines for two use cases and performed a thorough data assessment, including end-state data architecture and data landscape assessment. The project was a huge success, delivering a great client experience and creating an incredible positive impact on the business.
I never imagined I would develop software and data engineering pipelines in such an environment. I was on the front lines with the client, at the true source of the problem, and ready to make the most of this experience–the good, the bad, and the messy.
Advice for recruits
I was nervous when preparing for my interviews, as I had only participated in technical interviews before and had no practice with case study questions. However, I quickly learned McKinsey’s interviewers want you to succeed and will support you when you’re stuck. My advice is to walk through your issues and solutions with the interviewers, ask clarifying questions and have a peer-to-peer discussion.
Take a look at some of McKinsey’s digital work and the different digital roles and people at McKinsey for a greater understanding of the type of work. Don’t hesitate to ask your interviewer specific questions about roles, people, the work and purpose of McKinsey or anything you’d like clarity on.
Sohum is a data engineer in Bangkok. Before McKinsey, Sohum was a software engineer with Agoda, an online travel agency, where he worked on big data products. He has a passion for the startup ecosystem, and once launched a happy hour directory startup.Sohum has a bachelor’s in computer science from Mahidol University in Thailand.
For more information on McKinsey's data engineering career paths, visit mckinsey.com/TechCareers.