Senior Data Analyst, BI & Reporting

As a Senior Data Analyst, BI & Reporting at MongoDB, you will primarily build insightful dashboards, define KPIs with functional analysts, provide analytical support to stakeholder teams, and tackle ad-hoc data queries. This role aims to empower stakeholders with automated, self-service data tools while enhancing business decision-making processes.

To qualify for the Senior Data Analyst, BI & Reporting role at MongoDB, candidates should have 4+ years of analytics experience, advanced SQL skills, and extensive proficiency in Tableau or similar visualization tools. Familiarity with Python or R is a plus, as is the ability to communicate effectively with stakeholders across various levels.

In the Senior Data Analyst, BI & Reporting role at MongoDB, you will use advanced SQL for data manipulation, along with Tableau for visualization. Collaboration with Data Architecture and Analytics Engineering teams may also require using various data processing and automation tools to optimize reporting processes.

Yes, the Senior Data Analyst, BI & Reporting position at MongoDB is a remote role based in Brazil, allowing you to work from the comfort of your own space while contributing to a global team.

MongoDB is dedicated to employee growth, offering a supportive culture that includes various professional development resources, employee affinity groups, and generous parental leave policies to ensure all employees thrive both personally and professionally.

In your response, highlight specific projects where you used Tableau to create impactful dashboards. Discuss your design choices, how you tailored visualizations to meet stakeholder needs, and the positive outcomes that resulted from your work.

Explain your process for collaborating with stakeholders to identify key business objectives, using data to inform your selections, and ensuring that KPIs are measurable and relevant to ongoing business needs.

Share a specific instance where you analyzed a large dataset, identified trends, and presented your findings in a way that influenced business strategy. Highlight the tools you used and the impact of your insights.

Discuss a situation where you had to work with incomplete information or unclear requirements. Explain how you sought clarification, utilized your analytical skills to fill gaps, and navigated toward successful project completion.

Talk about your strategies for simplifying complex data concepts, such as using analogies or visual aids. Share examples where clear communication facilitated better understanding and decision-making among stakeholders.

Provide details about your level of SQL proficiency, specific tasks you’ve performed, and any challenges you faced in manipulating large datasets. Emphasize how you overcame such challenges to deliver valuable insights.

Discuss your approach to assessing the urgency and impact of requests. Explain your method for balancing short-term and long-term projects, and how clear communication with stakeholders helps you manage expectations.

Outline the steps you take to verify data integrity, including validation processes and cross-referencing data sources. Mention any tools or techniques you use for data cleaning and ensuring precision in your analysis.

Share your experience with identifying manual processes that could benefit from automation, including the tools and technologies you used. Highlight specific successful automation projects and their efficiency gains.

In your answer, express your admiration for MongoDB's innovative approach to data and software. Discuss how the role aligns with your career goals, your passion for data analytics, and how you aim to contribute to the company's mission.