Analytics Engineer, Business Intelligence

As an Analytics Engineer in Business Intelligence at Bitpanda, you will be responsible for driving data-driven decision-making across various teams. This includes contributing to the design of core data models, unifying business intelligence with stakeholders, identifying reporting needs with Finance and Operations, maintaining high data quality using dbt with Python and SQL, and streamlining dashboard creation. Your role is crucial in helping different departments understand the metrics that impact millions of end users worldwide.

To succeed as an Analytics Engineer in Business Intelligence at Bitpanda, candidates should have advanced experience with SQL, dbt, and Python. Hands-on experience with tools like Airflow and BI platforms such as Tableau or Metabase is advantageous. A strong foundation in data modelling, data quality frameworks, and data visualization is also essential, along with around three years of professional experience in analytics engineering or business intelligence and a degree in computer science, business informatics, applied mathematics, or statistics.

The Analytics Engineer role at Bitpanda significantly contributes to the company's mission by ensuring that data informs strategic decisions across the organization. By working collaboratively with various teams, you will help drive insights that focus on growth and enhance the overall user experience for millions of customers. Your expertise will empower other analysts to harness data effectively, ultimately supporting Bitpanda's goal of being Europe’s leading investment platform.

In your role as an Analytics Engineer in Business Intelligence at Bitpanda, you will primarily utilize SQL, dbt, and Python for data management and modeling. Additionally, tools like Airflow for workflow management and Business Intelligence software such as Tableau or Metabase will facilitate your ability to create insightful dashboards and reports. These tools will enable you to maintain high data quality and support stakeholders with actionable insights.

Bitpanda fosters a vibrant and inclusive company culture that emphasizes collaboration, innovation, and growth. As an Analytics Engineer, you’ll work in a diverse environment that encourages creativity and open communication. The flexibility-first approach allows you to balance in-office and remote work while participating in both virtual and in-person company-wide events. Bitpanda's commitment to building a team with varied backgrounds and perspectives further enriches the workplace atmosphere.

When answering this question, reflect on specific projects where you utilized SQL to extract, manage, and analyze data. Highlight your proficiency in writing complex queries, optimizing performance, and ensuring data accuracy. Relate your skills back to how they've contributed to business intelligence efforts in your previous roles.

Discuss your familiarity with different data visualization tools like Tableau or Metabase. Explain your rationale for choosing a specific tool based on project requirements, such as audience needs, the complexity of data, and desired visualization types. Providing examples of successful projects will strengthen your response.

To ensure data quality, emphasize the frameworks and practices you implement, such as routine data validation checks, consistent data cleaning processes, and leveraging dbt models. Explain how these practices contribute to accurate and reliable insights that guide decision-making.

Share a specific scenario where you worked with colleagues from different teams such as Finance or Operations. Describe the challenge, your role in coordinating efforts, and the successful outcome. Highlight your communication and problem-solving skills during this collaboration.

Detail your method for creating core data models, including identifying business requirements, understanding data sources, and applying best practices in data modeling, such as dimensional modeling. Discuss the importance of aligning models with business needs to support analytics effectively.

Illustrate your commitment to professional growth by mentioning resources you follow, such as industry publications, online courses, or webinars. Emphasize the importance of continuous learning in a rapidly evolving field and how you've applied new knowledge to your work.

Provide a clear, structured narrative about a specific project where you enhanced a reporting process. Describe the initial challenges, the actions you took to implement improvements, and the measurable impacts those changes had on efficiency and decision-making.

Reflect on common challenges like data inconsistencies or integration issues. Discuss specific examples of how you identified these challenges and the strategies you employed to resolve them, highlighting your analytical skills and persistence.

Describe your systematic approach, including defining the problem, gathering data, engaging stakeholders, and formulating a process for analysis. Emphasize the importance of understanding the business context and collaborating with relevant teams to ensure alignment and clarity.

Discuss your passion for innovation and the transformative potential of technology in improving financial services. Highlight specific interests in how analytics can empower users and enhance their financial experiences, linking it back to your desire to contribute positively to the industry.