Senior Data Analyst

Skills this role screens for

About the role

This Sr Data Analyst will join our analytics org within the Executive Insights team, which is responsible for synthesizing revenue and operational data from across the company to measure the trajectory and overall health of the business.

You will work closely with partner teams in Analytics, FP&A, Accounting, Cloud Billing, and Sales Operations to not only drive alignment on business performance narratives, but also to drive company wide transparency and data democratization for company key metrics.

Data pipelines, visualizations, root cause analyses, and deep dives generated by this team routinely empower MongoDB’s executive team to make data-informed decisions. This is a high visibility role that offers exposure to senior leadership via the team’s support of the office of the CFO.

We are looking to speak to candidates who are based in Gurugram for our hybrid working model.

The work

Responsibilities

• Deep dive on performance metrics from across the company to surface drivers of business growth to enable data-driven decision making at the executive level
• Produce insights to answer requests ahead of critical reporting periods, including earnings and investor days
• Partner with the rest of the team to own the end-to-end delivery of recurring consumption and revenue reports (weekly, monthly, and quarterly) ensuring they're accurate, timely, and trusted by stakeholders
• Proactively identify and fix data quality issues, broken pipelines, or reporting discrepancies
• Document metric definitions, report logic, and data lineage

Who they want

Skills & Attributes

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 3273559476

• The ideal candidate excels equally in data wrangling, pipelining, and storytelling, and shares a passion for automation and continuous process improvement
• 4+ years in an analyst, data, or BI role with meaningful ownership of key business metrics reporting
• Strong SQL skills; comfortable writing and optimizing queries against large-scale warehouses (Trino, BigQuery, or similar)
• Working proficiency in Python for data transformation, automation, or analysis
• Hands-on Tableau or similar BI tool experience
• Experience with agent-driven development practices
• Experience working with consumption-based or usage-based revenue data (subscription, metered billing, or usage analytics a strong plus)
• Nice-to-have: exposure to analytics engineering practices (dbt, data modeling, testing frameworks)
• And most importantly, passionate about using data to help guide strategic decision making