Data Analyst

As a Data Analyst, you will be responsible for structuring and analyzing our mobile app data, designing taxonomy systems, developing monitoring systems for data quality, and creating interactive dashboards using tools like Apache Superset. Your role also involves optimizing SQL queries for reporting and collaborating with external developers to manage data analytics processes.

To qualify for the Data Analyst position, we prefer candidates with a Bachelor's degree in Computer Science, Data Science, Statistics, or a related field. We are looking for individuals with at least 3 years of experience in data analytics, ideally within the mobile app or gaming industries, coupled with strong SQL skills and familiarity with tools like Apache Superset.

Essential skills for our Data Analyst role include advanced knowledge of Snowflake, SQL proficiency, hands-on experience with BI tools like Apache Superset, and a strong understanding of data quality monitoring methods. Additionally, excellent communication and stakeholder management skills are crucial for effectively conveying technical concepts to a diverse audience.

We value self-starters with a proactive mindset who can identify opportunities and solve challenges independently. Exceptional communication skills and the ability to bridge technical and business perspectives are crucial for our Data Analyst role, as is a solution-oriented attitude towards data-related issues.

Our Data Analysts enjoy a range of benefits, including private health insurance for your peace of mind, meal and transportation allowances to ease your daily commute, a cozy office environment filled with snacks, and a learning stipend to support your professional development.

When answering this question, highlight specific projects where you designed and implemented a data taxonomy system. Share your thought process in organizing complex data and how it improved data accessibility and analysis.

Discuss your approach to monitoring data pipelines and the tools you have utilized, such as AWS or Snowflake services, to ensure data integrity. Share any methodologies or techniques you’ve employed effectively in past roles.

Your answer should cover techniques you’ve used to enhance SQL performance, such as indexing, query restructuring, or utilizing denormalized data models. Provide examples of challenges you faced and the solutions you implemented.

In your response, share specific projects where you designed interactive dashboards and the impact they had on decision-making. Discuss how you choose the right visualizations based on the data at hand.

Convey your strategies for simplifying complex data insights, such as using visual aids, analogies, or clear documentation. Highlight instances where this has been particularly successful in fostering collaboration.

Share your experiences working with developers and how you establish requirements for collaborative projects. Emphasize the importance of clear communication and alignment on project goals.

Reflect on a specific challenge, outlining the context, your analysis, and the steps you took to arrive at a solution. This demonstrates your problem-solving skills and capacity to think critically.

Discuss your methods for ongoing learning, whether through online courses, reading industry blogs, attending webinars, or participating in data analytics communities. This shows your commitment to professional growth.

Talk about your favorite tools, such as Apache Superset, and provide reasons for your choices based on usability, features, and past experiences that highlight their effectiveness.

Describe your approach to task management, such as using prioritization frameworks or collaboration with team members to align on urgency and importance, ensuring that critical analyses are performed in a timely manner.