Manager, Data Engineering (Hybrid in Bangalore)
SmartsheetBangalore, INDIAPosted 12 March 2026
Job Description
For over 20 years, Smartsheet has helped people and teams achieve–well, anything. From seamless work management to smart, scalable solutions, we’ve always worked with flow. We’re building tools that empower teams to automate the manual, uncover insights, and scale smarter. But more than that, we’re creating space– space to think big, take action, and unlock the kind of work that truly matters. Because when challenge meets purpose, and passion turns into progress, that’s magic at work, and it’s what we show up for everyday.
For over 20 years, Smartsheet has helped people and teams achieve–well, anything. As the Intelligent Work Management Platform, we are redefining the velocity of work by uniting people, data, and AI to move businesses forward. We don’t just automate tasks; we eliminate execution silos and turn strategic vision into measurable enterprise impact. We’re creating a space to think big and take action, because when challenge meets purpose and AI-powered execution meets human ingenuity, that’s magic at work. It’s what we show up for every day, helping organizations not just keep up with change, but thrive because of it.
Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for a Manager, Data Engineering who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.
You Will:
Focus on team members and coaching them to play to their strengths, grow and deliver peak performance
Lead and mentor a team of data engineers and operations specialists.
Define and govern solutions for data platform ensuring scalability, cost-efficiency, and reliability
Develop and maintain data platform, including CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines
Delegate and harness the aggregate strength of your team.
Focuses on individual and team needs to foster a positive culture consistent with Smartsheet values.
Actively helps individuals and the overall team to set priorities and focus on delivery of commitments
Review team's designs and provide feedback on deployment safety, resilience, scale, performance, and security
Lead and facilitate cross-team interactions, communication, and dependencies
Ensure all changes are fully tested before being deployed
Ensure deployment plans are well-considered and include appropriate scalability and load tests
Facilitate feedback and discussions with Product and Engineering teams on customer needs, user experience, implementation efficiency, and performance
Work with stakeholders to align data platform with business strategies.
Ensure all AI applications adhere to regulatory compliance, security, and ethical guidelines
Drive Engineering and Operational excellence initiatives
Perform other duties as assigned
You Have:
Enterprise SaaS software solutions with high availability and scalability
Experience building teams through recruiting and retention
Experience in Leading and Mentoring a team of Data engineers and DevOps engineers.
Solution handling large scale structured and unstructured data from varied data sources
Experience in building and maintaining Data platform systems ensuring scalability, reliability, efficiency and security
Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
Databricks Lakehouse , Medallion Architecture, Unity Catalog, Snowflake
Experience in Data Governance ensuring data quality, freshness, integrity
Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
Programmi ... (truncated, view full listing at source)
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