Dashboarding Data Engineer

# Summary

We are seeking a highly skilled and experienced Senior Dashboarding Data Engineer to join our dynamic team. This role is pivotal in transforming complex data into clear, actionable business insights through the design and delivery of impactful dashboards. The ideal candidate will leverage their expertise in SQL and Power BI to build semantic models, map data to key performance indicators (KPIs), and develop scalable reporting solutions. Working closely with stakeholders, the engineer will ensure that dashboards effectively visualize critical metrics such as usage, cost, and performance. Additionally, the role supports the integration of AI/ML models to enable conversational data access while maintaining strict adherence to data governance and security standards.

Responsibilities

• Design, develop, and maintain interactive and insightful dashboards that translate raw data into meaningful business insights, focusing on usage, cost, and performance metrics.
• Map complex datasets to key performance indicators (KPIs) to provide clear, actionable metrics aligned with business goals.
• Build and optimize semantic data models that enable scalable and efficient reporting solutions, primarily using SQL and Power BI.
• Collaborate closely with cross-functional stakeholders—including business analysts, data scientists, and product managers—to gather requirements, validate data accuracy, and ensure dashboards meet user needs.
• Support the integration of AI/ML models into dashboarding solutions to facilitate conversational and advanced data access capabilities.
• Ensure all dashboarding and data engineering activities comply with organizational data governance policies and security standards.
• Continuously monitor and improve dashboard performance, usability, and data quality.
• Provide mentorship and guidance to junior data engineers and analysts, fostering a culture of data-driven decision-making.
• Stay current with industry trends and emerging technologies in data visualization, dashboarding, and AI/ML integration to recommend and implement best practices.
• Participate in agile development processes, including sprint planning, code reviews, and retrospectives, to deliver high-quality solutions on time.

Requirements

Must-Have Skills

• SQL: Expert-level proficiency in SQL for querying, transforming, and optimizing large datasets across relational databases. Ability to write complex queries, stored procedures, and optimize performance in cloud-based data warehouses.
• Power BI: Extensive experience designing and developing interactive dashboards and reports using Power BI. Skilled in data modeling, DAX calculations, and creating user-friendly visualizations that drive business insights.
• Data Mapping to Business KPIs: Proven ability to translate business objectives into measurable KPIs and map raw data accordingly. Experience working with stakeholders to define and refine KPIs that align with strategic goals.
• Dashboard Design: Strong skills in dashboard design principles, including usability, accessibility, and storytelling with data. Ability to create intuitive interfaces that enable users to explore data and derive insights independently.
• Semantic Modeling: Experience building semantic data models that abstract complex data structures into business-friendly formats, enabling scalable and maintainable reporting solutions.
• Stakeholder Engagement: Excellent communication and collaboration skills to work effectively with diverse teams and stakeholders. Ability to gather requirements, present findings, and incorporate feedback to ensure dashboard relevance and accuracy.

Nice-to-Have Skills

• BigQuery: Familiarity with Google BigQuery for managing and querying large-scale datasets in a cloud environment. Experience optimizing queries and integrating BigQuery with BI tools.
• Databricks AI/BI: Knowledge of Databricks platform capabilities for AI and BI workloads, including data engineering pipelines and collaborative analytics.
• Looker: Experience with Looker as a BI tool, including LookML modeling and dashboard/report creation. Understanding of Looker’s semantic modeling approach is a plus.
• AI/ML Model Integration: Exposure to integrating AI/ML models into dashboarding solutions to enable advanced analytics and conversational data access. Understanding of how to operationalize models within BI platforms.