BI Engineer

As a BI Engineer at Teikametrics, you will develop and maintain scalable dashboards and reports in Looker, utilizing LookML for efficient data modeling. Your responsibilities include writing optimized SQL queries, collaborating with stakeholders to gather business requirements, analyzing data for insights, and maintaining a centralized data model. You will also conduct performance tuning and champion best practices in data visualization, ensuring that the data stories we tell are impactful and clear.

To be considered for the BI Engineer role at Teikametrics, candidates typically need a Bachelor’s degree in Computer Science, Data Science, Information Systems, or a closely related field. Additionally, 3-5 years of experience in BI engineering or as a LookML developer is essential. Proficiency in Looker and LookML, as well as a strong command of SQL, will significantly strengthen your application.

A BI Engineer at Teikametrics should be well-versed in Looker and LookML for building and managing data visualizations and models. Additionally, a strong understanding of SQL is crucial for extracting and analyzing data. Familiarity with data analytics, data modeling concepts, and the ability to visualize data effectively will also be beneficial for excelling in this position.

Yes, Teikametrics offers the flexibility for BI Engineers to work remotely. We value work-life balance and provide the option to work from home or any location, along with a remote working allowance to support your productivity and comfort in a flexible work environment.

Teikametrics is committed to the professional development of its employees. As a BI Engineer, you will have access to training and development allowances to expand your skill set. The fast-paced nature of a growing company like Teikametrics offers numerous opportunities for advancement and the chance to work on innovative projects that leverage the latest trends in BI tools and analytics.

In your response, detail your specific roles and projects where you utilized Looker and LookML. Highlight your familiarity with building data models and visualizations, and share how your contributions led to improved business insights or decision-making.

Discuss methods such as indexing, avoiding SELECT *, and using appropriate joins to enhance query performance. Providing specific examples of how you improved query speeds or handled large datasets will showcase your expertise.

Explain your review process for data entry and reporting. Discuss the checks and balances you implement, such as validating sources, cross-referencing with other datasets, and how you use automated testing to maintain high data integrity.

Share a relevant experience where you communicated technical concepts to non-technical people effectively. Highlight your approach to gathering requirements to ensure their needs were met and how you translated those requirements into actionable technical solutions.

Talk about principles such as clarity, accuracy, and storytelling in visualizations. Discuss how you choose the right types of charts or graphs for different data scenarios and how you prioritize user friendliness in dashboard design.

Mention resources like blogs, online courses, webinars, and industry conferences that you follow. Highlight your proactive approach to professional development in the rapidly evolving field of BI.

Provide a specific challenge you've encountered, such as dealing with incomplete data or performance issues. Explain how you approached the problem, what solutions you implemented, and the outcomes of these actions.

Discuss your time management and prioritization skills. Explain how you break down projects into manageable tasks, your methods for keeping stakeholders informed, and how you ensure quality delivery even under pressure.

Describe a specific project, including its goals, the approaches you took, and the results achieved. Highlight how your insights influenced business strategy or outcomes to demonstrate your impact as a BI Engineer.

Outline a systematic approach for troubleshooting, including identifying the problem, looking at potential data sources, validating the data flow, and collaborating with teams to resolve it. Provide a specific example where you effectively mitigated an issue.