As a Senior Engineering Manager in the Cleanroom team, you will lead a high-performance engineering organization building scalable data intensive platforms, operating at a platform and organization-wide level, driving architecture and technical strategy. You will define engineering architecture and standards, influence long-term platform direction, coach engineers, own the delivery and ensure the Cleanroom platform scales securely and reliably to support sustained business growth.

Responsibilities

- Lead, mentor and grow a team of data-platform engineers delivering critical platform capabilities.
- Own the execution, delivery predictability and the technical quality.
- Lead organization-wide technical initiatives focused on performance optimization, scalability, reliability, security, governance, and cost efficiency.
- Review and influence critical architectural decisions across teams, establishing engineering best practices and architectural governance standards across cloud platforms, primarily AWS, with exposure to Azure and GCP and using Databricks.
- Partner closely with global engineering, product management, architecture, and business stakeholders to align technical solutions with strategic business objectives.
- Own the end-to-end software development lifecycle, including requirements gathering, solution design, development, deployment, observability, and documentation.
- Mentor and guide senior and junior engineers, fostering a culture of innovation, accountability, collaboration, and technical excellence.

Qualifications
- B.E/B.Tech/M.Tech/MCA in Computer Science, Information Technology or a related field.
- 12-16 years of strong software engineering experience,



with 3-4+ years of experience in managing and leading large scale data engineering teams.
- Ability to lead a high performing team, mentor the engineers and develop them as future technical leaders.
- Deep expertise in Data Warehousing, Data Lakes, Delta Lake architecture, and modern big data ecosystems, with strong hands-on experience in Databricks, Python, PySpark, and Apache Spark for building high-performance distributed data processing solutions at scale.
- Working knowledge of TypeScript, Node.js, and UX development, with strong expertise in AWS services (S3, Glue, Redshift, EMR, Athena, Lambda, and EventBridge) for building scalable, cloud-native data platforms.
- Experience with real-time and near real-time data streaming technologies (Kafka, AWS Kinesis, SQS, RabbitMQ) and strong expertise in relational and NoSQL databases, including PostgreSQL, SQL Server, Aurora, RDS, MongoDB, and DynamoDB.
- Strong understanding of CI/CD and DevOps practices using tools such as Jenkins, Github/GitLab, Bitbucket, GoCD and automated deployment pipelines.
- Proven ability to influence technical direction, drive cross-functional initiatives, and lead complex engineering programs at scale.
- Exposure to Generative AI technologies including LLMs, RAG architectures, and Agentic AI systems, with experience designing and deploying AI-driven solutions.

Nice to have
- AWS and Databricks certifications and experience with Azure / Google Cloud Platform (GCP).
- Experience building data platforms in privacy-protected or cleanroom environments.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior Manager Software Engineering (Bengaluru)
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