Principal Data Engineer / Architect - Individual Contributor
For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it's what we show up for every day. 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 Principal Data & AI/ML Ops
Engineers, 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:
Data Architecture and Design : Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation's data infrastructure
Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
Perform other duties as assigned
You Have:
Enterprise SaaS software solutions with high availability and scalability
Solution handling large scale structured and unstructured data from varied data sources
Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
Programming languages like Python, SQL, and potentially Java or Scala
Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform) , Observability, monitoring and alerting
Solution Cost Optimisations and design to cost
Driving engineering excellence initiatives
Legally eligible to work in India on an ongoing basis
Get to Know Us:
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You'll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you're doing work that stretches you, excites you, and connects you to something bigger, that's magic at work. Let's build what's next, together.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Enterprise SaaS software solutions with high availability and scalability
Solution handling large scale structured and unstructured data from varied data sources
Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
Programming languages like Python, SQL, and potentially Java or Scala
Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform) , Observability, monitoring and alerting
Solution Cost Optimisations and design to cost
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