Principal Data Platform Engineer (Bengaluru)
Okta · Bengaluru · 10+ yrs experience · Posted 2026-07-18
Tech stack: AWS, Terraform
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About the role
Responsibilities:
- Own the technical strategy and implementation for the company's AI data platform, translating product requirements into a concrete technical vision centered on Snowflake, AWS, dbt.
- Design and implement a robust security and governance framework as a core pillar of the platform, ensuring our high-compliance, high-security standards are met.
- Build automated solutions for data classification, access control, and vulnerability management (Nessus/Qualys), ensuring data is secure and trusted for AI consumption.
- Implement and manage the strategy for infrastructure as code (Terraform) and CI/CD (GitHub/GitLab) to ensure secure, reproducible, and auditable deployments.
- Set the bar for engineering excellence, driving best practices in code quality, system design, and operational readiness.
- Serve as an engineering partner to the Principal Product Manager, providing technical feasibility, scoping, and architectural guidance.
- Communicate technical vision, strategy, and trade-offs clearly to senior leadership and cross-functional teams.
- Collaborate with the AI, security, and analytics teams to ensure the data platform meets the complex needs of the entire business.
- What You Bring
- Experience: 10+ years of data engineering experience, with at least 5 years focused on architecting data platforms for data products, analytics, and/or AI-driven products.
- Experience with high-compliance/high-security regulated environments is a plus.
- Technical Authority: Deep and recognized mastery of data platforms and architecture, including cloud applications like Snowflake, Databricks, and AWS.
- Expert-level understanding of data pipeline and orchestration tools like dbt, Airflow, Fivetran, and Terraform.
- Security & Governance DNA: Deep expertise in designing and implementing technical frameworks for data governance, access control, and security within a modern data stack.
- Cross-Functional Partnership: A proven track record of partnering successfully with product management and business leaders to translate vision into high-impact technical solutions.
- Balance of Today vs.
- Tomorrow: Ability to deliver immediate, high-quality engineering solutions while building a scalable and maintainable foundation for future innovation.
- What Success Looks Like
- A secure, scalable, and elegantly designed AI data platform that serves as the trusted data foundation for the company.
- Robust, automated data governance and security frameworks embedded into the platform's core architecture.
- A well-architected and cost-optimized tech stack that accelerates development and reduces operational friction.
- Elevated technical capabilities and engineering excellence across the team, driven by your mentorship and leadership.
- LI_Hybrid
- P24713_3369501
- Supporting Your Well-Being
- Driving Social Impact
- Developing Talent and Fostering Connection + Community
Qualifications:
- into a concrete technical vision centered on Snowflake, AWS, dbt.
- Design and implement a robust security and governance framework as a core pillar of the platform, ensuring our high-compliance, high-security standards are met.
- Build automated solutions for data classification, access control, and vulnerability management (Nessus/Qualys), ensuring data is secure and trusted for AI consumption.
- Implement and manage the strategy for infrastructure as code (Terraform) and CI/CD (GitHub/GitLab) to ensure secure, reproducible, and auditable deployments.
- Set the bar for engineering excellence, driving best practices in code quality, system design, and operational readiness.
- Serve as an engineering partner to the Principal Product Manager, providing technical feasibility, scoping, and architectural guidance.
- Communicate technical vision, strategy, and trade-offs clearly to senior leadership and cross-functional teams.
- Collaborate with the AI, security, and analytics teams to ensure the data platform meets the complex needs of the entire business.
- What You Bring
- Experience: 10+ years of data engineering experience, with at least 5 years focused on architecting data platforms for data products, analytics, and/or AI-driven products.
- Experience with high-compliance/high-security regulated environments is a plus.
- Technical Authority: Deep and recognized mastery of data platforms and architecture, including cloud applications like Snowflake, Databricks, and AWS.
- Expert-level understanding of data pipeline and orchestration tools like dbt, Airflow, Fivetran, and Terraform.
- Security & Governance DNA: Deep expertise in designing and implementing technical frameworks for data governance, access control, and security within a modern data stack.
- Cross-Functional Partnership: A proven track record of partnering successfully with product management and business leaders to translate vision into high-impact technical solutions.
- Balance of Today vs.
- Tomorrow: Ability to deliver immediate, high-quality engineering solutions while building a scalable and maintainable foundation for future innovation.
- What Success Looks Like
- A secure, scalable, and elegantly designed AI data platform that serves as the trusted data foundation for the company.
- Robust, automated data governance and security frameworks embedded into the platform's core architecture.
- A well-architected and cost-optimized tech stack that accelerates development and reduces operational friction.
- Elevated technical capabilities and engineering excellence across the team, driven by your mentorship and leadership.
- LI_Hybrid
- P24713_3369501
- Supporting Your Well-Being
- Driving Social Impact
- Developing Talent and Fostering Connection + Community
Qualifications
- into a concrete technical vision centered on Snowflake, AWS, dbt.
- Design and implement a robust security and governance framework as a core pillar of the platform, ensuring our high-compliance, high-security standards are met.
- Build automated solutions for data classification, access control, and vulnerability management (Nessus/Qualys), ensuring data is secure and trusted for AI consumption.
- Implement and manage the strategy for infrastructure as code (Terraform) and CI/CD (GitHub/GitLab) to ensure secure, reproducible, and auditable deployments.
- Set the bar for engineering excellence
- driving best practices in code quality, system design, and operational readiness.
- Serve as an engineering partner to the Principal Product Manager, providing technical feasibility, scoping, and architectural guidance.
- Communicate technical vision, strategy, and trade-offs clearly to senior leadership and cross-functional teams.
- Collaborate with the AI, security, and analytics teams to ensure the data platform meets the complex needs of the entire business.
- What You Bring
- Experience: 10+ years of data engineering experience, with at least 5 years focused on architecting data platforms for data products, analytics, and/or AI-driven products.
- Experience with high-compliance/high-security regulated environments is a plus.
- Technical Authority: Deep and recognized mastery of data platforms and architecture, including cloud applications like Snowflake, Databricks, and AWS.
- Expert-level understanding of data pipeline and orchestration tools like dbt, Airflow, Fivetran, and Terraform.
- Security & Governance DNA:
- Deep expertise in designing and implementing technical frameworks for data governance, access control, and security within a modern data stack.
- Cross-Functional Partnership: A proven track record of partnering successfully with product management and business leaders to translate vision into high-impact technical solutions.
- Balance of Today vs.
- Tomorrow: Ability to deliver immediate, high-quality engineering solutions while building a scalable and maintainable foundation for future innovation.
- A secure, scalable, and elegantly designed AI data platform that serves as the trusted data foundation for the company.
- Robust, automated data governance and security frameworks embedded into the platform's core architecture.
- A well-architected and cost-optimized tech stack that accelerates development and reduces operational friction.
- Elevated technical capabilities and engineering excellence across the team, driven by your mentorship and leadership.
- LI_Hybrid P24713_3369501 Supporting Your Well-Being
- Driving Social Impact
- Developing Talent and Fostering Connection + Community
Responsibilities
- Own the technical strategy and implementation for the company's AI data platform, translating product requirements into a concrete technical vision centered on Snowflake, AWS, dbt.
- Design and implement a robust security and governance framework as a core pillar of the platform, ensuring our high-compliance, high-security standards are met.
- Build automated solutions for data classification, access control, and vulnerability management (Nessus/Qualys), ensuring data is secure and trusted for AI consumption.
- Implement and manage the strategy for infrastructure as code (Terraform) and CI/CD (GitHub/GitLab) to ensure secure, reproducible, and auditable deployments.
- Set the bar for engineering excellence
- driving best practices in code quality, system design, and operational readiness.
- Serve as an engineering partner to the Principal Product Manager, providing technical feasibility, scoping, and architectural guidance.
- Communicate technical vision, strategy, and trade-offs clearly to senior leadership and cross-functional teams.
- Collaborate with the AI, security, and analytics teams to ensure the data platform meets the complex needs of the entire business.
- What You Bring
- Experience: 10+ years of data engineering experience, with at least 5 years focused on architecting data platforms for data products, analytics, and/or AI-driven products.
- Experience with high-compliance/high-security regulated environments is a plus.
- Technical Authority: Deep and recognized mastery of data platforms and architecture, including cloud applications like Snowflake, Databricks, and AWS.
- Expert-level understanding of data pipeline and orchestration tools like dbt, Airflow, Fivetran, and Terraform.
- Security & Governance DNA:
- Deep expertise in designing and implementing technical frameworks for data governance, access control, and security within a modern data stack.
- Cross-Functional Partnership: A proven track record of partnering successfully with product management and business leaders to translate vision into high-impact technical solutions.
- Balance of Today vs.
- Tomorrow: Ability to deliver immediate, high-quality engineering solutions while building a scalable and maintainable foundation for future innovation.
- A secure, scalable, and elegantly designed AI data platform that serves as the trusted data foundation for the company.
- Robust, automated data governance and security frameworks embedded into the platform's core architecture.
- A well-architected and cost-optimized tech stack that accelerates development and reduces operational friction.
- Elevated technical capabilities and engineering excellence across the team, driven by your mentorship and leadership.
- LI_Hybrid P24713_3369501 Supporting Your Well-Being
- Driving Social Impact
- Developing Talent and Fostering Connection + Community