Data Engineer

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.

If you suspect a recruiting scam, please contact us at wwrecruitingteam@commvault.com

About Commvault

Commvault (NASDAQ: CVLT) is the gold standard in cyber resilience. The company empowers customers to uncover, take action, and rapidly recover from cyberattacks – keeping data safe and businesses resilient. The company’s unique AI-powered platform combines best-in-class data protection, exceptional data security, advanced data intelligence, and lightning-fast recovery across any workload or cloud at the lowest TCO. For over 25 years, more than 100,000 organizations and a vast partner ecosystem have relied on Commvault to reduce risks, improve governance, and do more with data.

Data Engineer

The Opportunity:

The Data Engineer is a critical member of the Business Intelligence and Analytics organization, responsible for architecting, building, and scaling enterprise data platforms that power advanced analytics and decision-making. This role focuses on designing and operationalizing robust, cloud-native data pipelines and data stores, ensuring reliable, high-quality, and governed data is available across the enterprise.

The Data Engineer partners closely with analytics, data science, and business teams to transform raw data into trusted, consumable assets. By leveraging modern data technologies and best practices, this role drives data accessibility, performance optimization, and scalability while enforcing strong data governance and quality standards.

What you’ll do…

Data Engineering & Pipeline Development

Design, build, and maintain scalable, reliable ELT/ETL pipelines across multiple data sources

Develop data ingestion frameworks for batch and near real-time data processing

Ensure data integrity through validation, monitoring, and error handling mechanisms

Optimize pipelines for performance, scalability, and cost efficiency

Data Modeling & Architecture

Design and implement logical and physical data models for analytics and reporting

Build and maintain data warehouses, data marts, and Lakehouse structures

Apply best practices in schema design (e.g., star/snowflake models)

Support enterprise data architecture initiatives and standards

Cloud Platform & Tools

Develop and optimize solutions using Azure Synapse, Azure Databricks, SQL Server, and related cloud services

Support and enhance data platform scalability, reliability, and performance

Leverage distributed processing frameworks (e.g., Spark) for large-scale data transformation

Data Quality, Governance & Reliability

Implement data quality checks, monitoring, and alerting for critical data assets

Ensure alignment with enterprise data governance, metadata, and security standards

Maintain data lineage and support auditability and compliance requirements

Uphold data accuracy, consistency, and availability SLAs

Analytics & BI Enablement

Deliver curated, modeled datasets to support BI tools such as Power BI

Partner with analytics teams to enable dashboards, reporting, and self-service analytics

Ensure data structures are optimized for performance and usability in reporting environments

Performance Optimization

Tune SQL queries, data models, and pipelines for optimal performance

Identify and resolve performance bottlenecks across data systems

Recommend improvements to data infrastructure and processing workflows

Cross-Functional Collaboration

Collaborate with business areas and BSA teams to align data requirements

Translate business needs into scalable and maintainable data solutions

Support project planning, requirements gathering, and solution design

Identify opportunities for process improvement and data-driven innovation

Engineering Best Practices

Follow best practices for version control, testing, and deployment of data pipelines

Contribute to CI/CD processes for data engineering workflows

Document data flows, models, and processes for maintainability and knowledge sharing

AI / ML & Advanced Analytics Enablement

Awareness of emerging AI/GenAI capabilities and their data requirements

Familiarity of integration patterns for Model Context Protocol (MCP) or similar tool-based interfaces, enabling AI agents and copilots to interact with enterprise data

Support integration of AI/ML solutions by enabling reliable data flows between enterprise data platforms and downstream applications

Support data requirements for model explainability, lineage, and governance

Exposure to tools such as Python (Pandas, NumPy), MLflow, or similar

Experience working with large-scale datasets for predictive or AI-driven applications

Who you are?

2-4+ years of experience in data engineering, BI/analytics engineering, or data architecture

Strong proficiency in SQL, data modeling, and performance tuning, aligning with the original expectations for SQL expertise.

Experience building and maintaining ETL/ELT pipelines

Hands-on experience with cloud data platforms (Azure preferred, including Synapse and Databricks)

Knowledge of data warehousing, data modeling, and database design

Experience with distributed data processing (e.g., Spark)

Experience with Power BI or similar BI tools

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field

Master’s degree in a relevant discipline is a plus

Certifications (Preferred)

Microsoft Azure Data Engineer Associate or similar cloud certification

Databricks or Spark-related certifications

Relevant certifications in data engineering, cloud platforms, or analytics

You’ll love working here because...

Continuous professional development, product training, and career pathing

Annual health check-ups, Tuition Reimbursement

An inclusive company culture, an opportunity to join our Community Guilds

Personal accident and Term life coverage

#LI-VK

Commvault’s goal is to make interviewing inclusive and accessible to all candidates and employees. If you have a disability or special need that requires accommodation to participate in the interview process or apply for a position at Commvault, please email accommodations@commvault.com For any inquiries not related to an accommodation please reach out to wwrecruitingteam@commvault.com.