Migration to cloud ecosystems like AWS is the need of the hour and it’s just the tip of the iceberg. As cloud adoption grows, data governance and security become increasingly important.
My last engagement was for a client that wanted to migrate its entire data ecosystem to cloud. It was a fascinating journey as we uncovered many intricacies behind their traditional data lake and developed ways to implement their existing practices with little or no differences on AWS.
Now, we’re helping this client develop stringent access processes for the cloud. We’re enabling proper data masking and encryption so their data, although physically away from their systems, is as secure as possible.
Data engineering at McKinsey
Our goal as data engineers is to help clients seamlessly and securely transition from on-premise services to cloud ecosystems by building reliable and easy-to-use data lakes and warehouses.
We transfer knowledge to and mentor our clients, so they are equipped to tackle challenges that come up down the line. This process of enabling clients has impressed me. It’s different from what I’ve seen and experienced elsewhere, and it has helped me build longer-lasting, deeper relationships with clients. It’s one of the things I love most about my job as a data engineer working in cloud.
Another special aspect of McKinsey is its awareness of tech trends and proactive moves to prepare its practitioners for the next big thing. A while back, we saw a lot of teams upskilling on tools like Tableau and Alteryx. Now, we’re seeing the focus shift to modern cloud technologies. The more we make ourselves competent in the intricacies of cloud services and analytics on cloud, the better we position ourselves to serve clients who need our help on such journeys. McKinsey’s ability to tap the latest tech and enable its workforce to pick it up has been something fascinating and something I have always admired about the firm.
Find a role in data engineering like Debanjan’s
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To see more of McKinsey’s latest research on the value available in the cloud and ways to capture it, visit cloud.mckinsey.com.