Business Intelligence Analyst

As a Business Intelligence Analyst at Showpad, your primary responsibilities include building dynamic dashboards using Amazon QuickSight, analyzing GTM data for trends and opportunities, designing data models and visualizations, and collaborating with various teams to ensure that reporting meets their needs. You will also produce scorecards for leadership, administer BI platforms, create impactful presentations, and train teams on BI tools.

To qualify for the Business Intelligence Analyst position at Showpad, candidates should possess 2-3 years of experience in Business Intelligence or Data Analytics, and have expertise in Amazon QuickSight. Additionally, proficiency in SQL, data modeling, and advanced Excel/Google Sheets is required. A Bachelor’s degree in a relevant field such as Data Science or Marketing Analytics is also essential.

Essential tools for the Business Intelligence Analyst role at Showpad include AWS QuickSight and AWS Athena to build dashboards and process data. Experience with GitLab is also required, while familiarity with other BI tools like Tableau or Power BI would be advantageous.

Successful Business Intelligence Analysts at Showpad need strong problem-solving abilities, a keen attention to detail, and excellent communication skills to present insights clearly. Additionally, the ability to train teams on BI tools and adapt to complex business challenges is crucial.

Showpad is committed to the professional development of its employees, including Business Intelligence Analysts, offering opportunities for continuous learning, training on new tools, and paid time off for volunteering. This supportive environment helps foster growth and engagement within the team.

When answering this question, highlight specific projects where you’ve used Amazon QuickSight to create dashboards or visualizations. Discuss the data sources you integrated and how your insights helped drive decisions, making sure to quantify the impact where possible.

To effectively answer this, explain your step-by-step data analysis process, including how you identify trends or anomalies and the tools you use for visualization. Share an example where your analysis directly influenced a business decision.

Highlight specific metrics such as conversion rates, customer acquisition costs, and customer lifetime value. Discuss how monitoring these metrics can provide insights into the effectiveness of GTM strategies and help identify opportunities for improvement.

Discuss your approach to prioritization, mentioning techniques like assessing the urgency and potential impact of each request. Emphasize your communication skills to manage expectations and ensure understanding among teams.

Share an experience where you successfully trained a team, focusing on your preparation methods, how you tailored the training to their level of understanding, and the feedback you received afterward which reinforced your training's impact.

Explain the importance of clarity and simplicity in data visualization. Mention tools you use and principles you follow, ensuring visuals communicate the intended message effectively and are tailored to the audience’s needs.

Detail your routine checks for data validation, including cross-checking data sources and implementing automated data quality checks. Convey the importance of accuracy in making informed business decisions.

Share a specific challenge where your analysis led to a solution, outlining the steps you took from data collection to presenting findings. Ensure to explain the positive outcome from your efforts.

Discuss various SQL queries you’ve written and how you’ve utilized data models to streamline reporting processes. Provide examples of how your skills have contributed to improving data accessibility and usability.

Articulate your commitment to continuous learning through online courses, webinars, and industry blogs. Mention any specific communities or resources you engage with to stay informed about the latest BI developments.