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Python, Parenting, and Patients

What started as a scroll on a job board, has now blossomed into a data engineering career at McKinsey in New York City. From helping save patient lives to raising a son, Sangeetha describes how McKinsey has helped her grow as a tech leader, healthcare engineer, and new mom.

As I was wrapping up my computer science master’s in 2015, I began searching for my next career move. At the time, I was a new mom, working as a senior data engineer at a healthcare not-for-profit, leading multiple analytics projects focused on medical code management.

I was looking for a niche opportunity to blend my existing work in healthcare with data engineering. Ultimately, I discovered a McKinsey healthcare data engineering position on a job board that seem to strike that perfect blend. I applied, was contacted by a McKinsey tech recruiter, and here I am.

Growth in healthcare and engineering

Since I started as a McKinsey senior data engineer (or analyst), I’ve been promoted to a data-engineering specialist, and now manager. I lead our data engineering and payment innovation team within the firm’s Healthcare practice.

I work extensively with people and play a significant role in the development and deployment of new tools. I work on topics ranging from value-based care to cost effectiveness and unit price normalization.

Video
What makes a data engineer like Sangeetha successful at McKinsey? In this video, she underlines the importance of technical strength, a zeal for collaborating with a diverse team, and an entrepreneurial spirit.

Combating COVID-19 and saving lives via Python

As a technology lead, a big part of my job is working with partners and stakeholders to understand their analytics needs and identify ways in which we can support them. Once I understand the scope of each project, I work with the rest of the team to architect and identify optimal solutions to shape the technology roadmap. We use Domo, Hive, PySpark, Python, SQL, Tableau, Talend, and others to build tools and products that deliver meaningful insights, and help drive organizational transformation. For example, one of my recent and most meaningful projects was helping to develop COVID-19 capacity modeling on primarily Python. Our solution analyzes hospital bed capacity and medical supply availability across various US states and internationally. It helps our clients better meet critical needs for COVID-19 patients. It’s one of the most impactful projects I’ve done because our analysis is positively impacting people’s lives, right now, as we still fight to get COVID-19 under control.

Video
In this video, Sangeetha shares how the blend of different tech backgrounds on her McKinsey team have exposed her to dozens of emerging tech platforms and languages. On the McKinsey healthcare projects she supports, akin to her COVID-19 work, that’s translated to positively affecting thousands – sometimes millions – of patients as a data engineer.

Giving back to our junior technologists

As a manager, I have the privilege of coaching and mentoring junior technologists on skills that can help them grow as engineers and aspiring tech leaders, such as different programming languages, finding balance, and effectively communicating to a tough stakeholder.

I am happy to give back, as McKinsey has provided me with ample training in data engineering, stakeholder communications, navigating the role of a manager, storylining, and even courses that go beyond the workplace, such as how to be a successful working mother. The level of leadership and tech learning I’ve had at McKinsey is simply unmatched.

Upskilling

Specifically, on the tech front, McKinsey offers access to an array of workshops, certifications (e.g., AWS, Azure, Hadoop, Oracle, Scrum, Spark, etc.), masterclasses, e-learnings (e.g., Udacity, DataCamp, Linux Academy), workshops, etc. to help data engineers upskill. I’ve personally taken our Kedro Bootcamp for Beginner Users, Docker Fundamentals, and Big Data on AWS, among others. Access to such workshops and on-the-job training have broadened my skills in data engineering and leadership. As I deepened my technical expertise and engineered new capabilities for our healthcare solutions, I was recognized with advancement opportunities.

Finding support as a tech leader and mom

New York City based Sangeetha is helping to save lives using Python to analyze hospital bed capacity and medical supply availability.
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People here, including firm partners, are open to positive change and feedback. They’re invested in my growth. They are understanding and genuinely caring. During these unprecedented times, we have been looking out for each other to make sure everyone is alright. I have leaned on McKinsey’s parents’ network to discuss challenges around work/life balance and childcare support.

Video
In this video, Sangeetha shares more about joining McKinsey while raising her infant (now six-year-old) son.

Outside of work

Sangeetha describes how McKinsey has helped her grow as a tech leader
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Outside of work, I love to pass the time ice-skating, playing tennis and volleyball, and enjoying time with my son. I’m also an active member of our Parents at McKinsey and Women in Tech communities.

Ultimately, at McKinsey, I’ve received the room, support, and resources to grow. It’s still a hard to believe that it all begin with a casual scroll on an online job board.

Find a job like Sangeetha’s

More about Sangeetha

Based in the New York City area, Sangeetha is a data engineering manager, specializing in the healthcare industry. Prior to McKinsey, she worked as a data engineer at AIG Insurance and the nonprofit, EmblemHealth. Sangeetha has also held data and systems engineering roles at IBM and Tata Consultancy Services in Chennai, India. She holds a bachelor’s in electronics and communication engineering from Anna University in Chennai, and a master’s in computer science from New York University.

For more information on McKinsey's data engineering career paths, visit mckinsey.com/TechCareers.

Note: All videos were filmed prior to the COVID-19 pandemic.