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Commvault (NASDAQ: CVLT) is a cyber resilience leader serving over 100,000 organizations globally. The company's AI-powered platform combines data protection, security, intelligence, and recovery capabilities across any workload or cloud.
The Senior Data Analytics Engineer is a hands-on senior individual contributor responsible for designing, developing, and operating governed analytics, semantic models, reusable business metrics, and AI-ready analytical assets. This role bridges analytics engineering, semantic modeling, business intelligence, data quality, and practical AI enablement to deliver trusted data products supporting reporting, decision-making, self-service analytics, and approved AI use cases.
Key responsibilities include:
**Analytics Engineering & Data Products**: Design and maintain semantic models, dimensional models, curated datasets, measures, KPIs, and hierarchies. Develop enterprise analytics solutions using SQL, Power BI, Microsoft Fabric, and Databricks. Optimize models for usability, scalability, and performance. Support dashboard developers and self-service users with well-documented assets.
**Applied Data Science & AI Readiness**: Apply statistical and machine learning knowledge to design analytics assets supporting downstream data science and AI. Partner with AI and Engineering teams to understand modeling and feature requirements. Develop feature-ready datasets and semantic structures for forecasting, segmentation, classification, and anomaly detection. Support generative AI and RAG solutions by preparing high-quality business definitions, metadata, and retrieval-ready content. Build knowledge graph and ontology-aligned data structures.
**AI Engineering & MLOps**: Build deployment pipelines for ML and generative AI workloads using version control, automated testing, and CI/CD. Support experiment tracking, model registration, inference, monitoring, and drift detection. Develop reusable feature and evaluation datasets. Implement automated tests for data, models, and production workflows.
**Governance & Quality**: Document business definitions, calculations, data sources, and dependencies. Partner with Data Governance on metadata, lineage, and access controls. Perform data profiling, reconciliation, and root-cause analysis. Ensure compliance with architecture, privacy, security, and responsible AI standards.
**Business Partnership**: Translate business questions into technical designs. Collaborate across Finance, GTM, Product, Customer, and People teams. Present findings to business and technical audiences. Mentor analysts and engineers on best practices.
**Requirements**:
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Analytics, Data Science, Mathematics, Statistics, or related quantitative/technical field
- Minimum 5 years professional experience in analytics engineering, business intelligence, semantic modeling, data engineering, or related discipline
- Advanced SQL expertise: complex query development, performance optimization, data profiling, reconciliation across large-scale enterprise datasets
- Experience designing and maintaining semantic models, dimensional models, metrics layers, KPIs, hierarchies, and governed business logic
- Hands-on experience with Power BI, Microsoft Fabric, Databricks, Spark, Python, or comparable modern data/analytics platforms
- Experience building curated analytical datasets, feature-ready data assets, and governed consumption layers for reporting, self-service analytics, data science, and AI
- Working knowledge of statistical analysis, machine learning concepts, feature engineering, model evaluation, and use cases (forecasting, segmentation, classification, anomaly detection, recommendation)
- Working knowledge of generative AI and retrieval patterns: LLMs, embeddings, vector search, RAG, prompt evaluation, AI agents
- Familiarity with knowledge graphs, ontologies, taxonomies, metadata, lineage, glossaries, and entity-relationship concepts
- Experience implementing data quality checks, validation routines, testing practices, documentation standards, and operational controls
- Experience partnering with cross-functional stakeholders to translate business definitions and requirements into scalable technical designs
- Strong written and verbal communication skills
**Preferred Skills**:
- Power BI semantic models, DAX, Microsoft Fabric, Databricks SQL, Unity Catalog, Microsoft Purview
- BI dashboard development; Power BI preferred, Tableau/Qlik acceptable
- Enterprise business applications: Salesforce, NetSuite, Marketo, Workday
- Knowledge graph, ontology, taxonomy, business glossary, entity resolution initiatives
- Retrieval-ready data, metadata, embeddings, vector search, RAG preparation
- Agile product/platform delivery with distributed teams
