Principal Data Analytics Engineer
Senior individual-contributor role at Commvault (Bangalore) defining enterprise standards for semantic models, governed metrics, and AI/MLOps engineering. Hands-on architecture using SQL, Power BI/Microsoft Fabric (DAX), and Databricks, plus GenAI patterns like RAG and vector retrieval, while mentoring engineers and leading design reviews.
- Compensation
- Not disclosed
- Location
- Bangalore, India
- Work setup
- Not specified
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Data analytics
- Posted
Skills
Must have
- 10+ years across analytics engineering, BI, semantic modeling, data engineering, ML engineering, or MLOps
- Principal-level technical leadership or architect experience for enterprise data, analytics, or AI solutions
- Deep expertise in SQL, dimensional modeling, semantic model design, performance optimization, and governed metrics
- Hands-on experience with Microsoft Power BI and/or Microsoft Fabric semantic models, including DAX
- Hands-on experience with Databricks or comparable cloud data and AI platform
- Experience with CI/CD, experiment tracking, model registries, monitoring, evaluation, and observability for ML or generative AI
- Working knowledge of generative AI patterns: embeddings, vector retrieval, RAG, prompt/model evaluation, agent-based solutions
- Understanding of metadata, lineage, data quality, access control, business glossary, and responsible AI
- Proven ability to mentor engineers, lead architecture reviews, and influence stakeholders without direct authority
- Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related field (or equivalent experience)
Nice to have
- Experience with Microsoft Purview, Unity Catalog, MLflow, Azure DevOps or GitHub Actions, and cloud observability tooling
- Experience supporting enterprise Finance, GTM, Product, Customer, or Workforce analytics domains
- Experience establishing reusable semantic or AI platform capabilities in a federated operating model
Full description
Recruitment Fraud Alert
We’ve learned that scammers are impersonating Commvault team members—including HR and leadership—via email or text. These bad actors may conduct fake interviews and ask for personal information, such as your social security number.
What to know:
- Commvault does not conduct interviews by email or text.
- We will never ask you to submit sensitive documents (including banking information, SSN, etc) before your first day.
- Commvault recruiters may contact prospective candidates through LinkedIn and other professional networking platforms regarding career opportunities. If you are unsure whether a recruiting communication is legitimate, review the profile to ensure they have a badge verifying them as a Commvault employee.
If you suspect a recruiting scam, please contact us at wwrecruitingteam@commvault.com
About Commvault
Commvault (NASDAQ: CVLT) delivers continuous recovery for the AI era. We help organizations stay ready for constant disruption by returning critical data, applications, identities, and AI systems to a clean, trusted state. Our purpose-built recovery solutions span cloud-native and hybrid environments, leveraging AI to enable resilience at enterprise scale.
The Opportunity:
The Principal AI & Semantic Engineer is the senior technical authority responsible for connecting governed enterprise data and business meaning with scalable analytics and artificial intelligence solutions. This role defines the architecture, standards, and engineering patterns for semantic models, governed metrics, AI-ready data products, machine learning operations, and generative AI consumption.
Operating at the intersection of Analytics, Data Engineering, Data Science, Governance, and AI Platform Engineering, this role ensures that enterprise data, metrics, models, and knowledge assets can be reliably discovered, understood, deployed, monitored, and reused. The Principal AI & Semantic Engineer provides hands-on technical leadership, guides complex implementations, and mentors engineers and analysts while remaining an individual contributor.
What you’ll do…Semantic Architecture & Governed Metrics
- Define enterprise standards and reference patterns for semantic models, dimensional models, business metrics, KPIs, hierarchies, calculations, and reusable analytical assets.
- Architect semantic consumption patterns across Microsoft Fabric, Power BI, Databricks Gold-layer data, and approved AI applications.
- Partner with business domain owners, analysts, and Data Governance to translate business concepts into consistent, governed definitions and analytical models.
- Lead design reviews for semantic models and analytical data products, balancing usability, reuse, performance, security, and maintainability.