Sanketh Balakrishna: The Engineering Leader Building the Foundations of Modern Data Infrastructure

From improving cloud database migration systems at AWS to architecting scalable data platforms at Datadog, Balakrishna’s work focuses on building the foundational infrastructure that enables modern cloud applications.

Modern software experiences often appear simple to users. A search result appears instantly, a dashboard refreshes with current information, or an application seamlessly accesses data across systems. Behind these experiences are complex engineering platforms responsible for moving, processing, and organising massive amounts of data reliably.

Developing these critical infrastructure systems has been the focus of Sanketh Balakrishna’s engineering career. As a Senior Engineering Manager at Datadog, Balakrishna has led the development and scaling of large-scale data infrastructure, including replication platforms, search systems, and distributed data technologies. His career reflects a consistent focus on solving one of the most challenging problems in modern cloud computing: enabling data to move efficiently and reliably between systems and regions while powering fast search experiences for users and downstream systems.

The importance of this work has grown as organisations increasingly operate distributed systems spanning multiple databases, regions, and applications. Data that once lived inside a single application now needs to power search experiences, analytics systems, customer-facing features, and internal platforms. Building infrastructure that enables this movement requires deep expertise in databases, distributed systems, reliability engineering, and platform design.

Balakrishna first addressed these challenges at Amazon Web Services (AWS), where he contributed to improving database migration capabilities for enterprises moving workloads to the cloud.

Engineering Cloud Migration Infrastructure at AWS

Database migration is one of the most operationally sensitive challenges in cloud computing. Large organisations often need to move critical data while minimising downtime and maintaining consistency between source and target systems.

At AWS Database Migration Service (AWS DMS), Balakrishna worked on improving the reliability and flexibility of large-scale database migrations.

One publicly documented contribution was the development of the Move Replication Task capability in AWS DMS. The feature enabled users to move an active replication task between replication instances while preserving migration progress. This addressed a practical operational challenge: migration infrastructure sometimes needs to change while migrations are already running, whether due to scaling requirements, maintenance, or resource optimisation.

Another publicly documented contribution was AWS DMS Auto Segmentation for MongoDB and Amazon DocumentDB migrations. As lead developer for this capability, Balakrishna designed and implemented a solution that improved migration performance by automatically dividing large collections into smaller segments that could be processed in parallel. These contributions were publicly documented through AWS Database Blog publications, where Balakrishna was mentioned as the lead developer for these capabilities. The work addressed practical challenges faced by organisations operating large-scale database migrations in cloud environments.

These projects demonstrate a broader engineering philosophy that has continued throughout Balakrishna’s career - infrastructure should not only function under normal conditions, but should also adapt to the operational realities of production environments.

Building Data Platforms for Modern Cloud Applications

After joining Datadog, Balakrishna expanded his focus from individual migration capabilities to broader platform engineering challenges.

As companies scale, engineering organisations often face a common problem: multiple teams independently build solutions for similar infrastructure needs. While these solutions may solve immediate requirements, they can create long-term complexity through duplicated systems, inconsistent operational practices, and increased maintenance costs.

Balakrishna focused on addressing this challenge by driving the development of a scalable approach to data replication infrastructure.

Balakrishna designed the foundation for reusable platform capabilities using modern data technologies, including change data capture (CDC) patterns, Debezium, and Kafka-based architectures, creating a scalable approach for supporting diverse replication workloads. Instead of treating replication as a collection of one-off pipelines, the platform approach aimed to provide engineering teams with reliable building blocks for moving data across systems. The engineering approach and architectural lessons from this work were also shared publicly through Datadog’s engineering blog, highlighting the challenges involved in building reliable replication infrastructure at scale.

The challenge was not simply moving records from one location to another. A production-scale replication platform must handle evolving schemas, failures, operational monitoring, and different requirements from multiple engineering teams.

By creating common infrastructure primitives, the platform enabled teams to focus more on product development while relying on a consistent foundation for data movement.

This reflects a broader shift happening across the technology industry: companies increasingly view internal platforms as strategic assets that accelerate engineering velocity.

From Technical Contributor to Engineering Leader

Beyond architecture and implementation, Balakrishna’s career has evolved into engineering leadership.

After joining Datadog as a Senior Engineer, he transitioned into engineering management and was promoted to Senior Engineering Manager in 2025. He now leads teams responsible for critical data and search infrastructure. His responsibilities expanded from designing systems to driving technical strategy, aligning teams, and enabling engineers to build scalable solutions.

Beyond replication, Balakrishna has expanded his impact across broader infrastructure challenges at Datadog. He has helped define architectural approaches for managing data across distributed environments, driving initiatives around global data platforms and search infrastructure, and guiding engineering teams toward solutions focused on scalability, reliability, and customer impact.

His approach to engineering leadership is rooted in the idea that the most impactful infrastructure work enables others to move faster.

“A strong replication and search platform can fundamentally accelerate the pace at which teams build and deliver new products,” Balakrishna says.

That philosophy captures the broader impact of platform engineering. The strongest infrastructure is often the infrastructure that allows engineering teams to build without needing to think about the complexity underneath.

Building the Future of Cloud Infrastructure

The next generation of cloud applications will depend increasingly on foundational systems that make data available, reliable, and actionable across complex environments.

From improving database migration capabilities at AWS to building scalable data platforms and leading infrastructure teams at Datadog, Sanketh Balakrishna’s work represents the type of engineering that powers modern software ecosystems.

While users may never directly see replication systems, data platforms, or search infrastructure, these technologies determine whether applications can operate reliably at global scale.

For engineers building the future of cloud computing, the challenge is not only creating new applications - it is creating the infrastructure layers that allow those applications to succeed.