BI Engineer (Temp to Hire Position)

Position Summary This BI Engineering role at Harness.io supports the Software Engineering Insights team by managing and optimizing a white-labeled Looker integration to deliver insightful, high-quality product analytics solutions. You’ll work to build and maintain data models, and ETL processes, leading to in-product dashboards, dashboarding templates and enhancing Harness’ Cloud Cost Management’s analytics capabilities About the role ● Manageandoptimize the Looker platform, integrated as a white-labeled solution within Harness.io’s Software Engineering Insights product. ● Collaborate with engineering, product, and data science teams to design and implement BI, data visualization, and analytics solutions aligned with product and business goals. ● Design and maintain scalable data models and ETL processes that support efficient data ingestion and transformation for reporting purposes. ● Develop and “washboard” data models, SQL transformations, and LookML objects, ensuring data quality and alignment with reporting requirements. ● Create and optimize Looker dashboards to support in-depth analysis, business KPIs, and real-time reporting, focusing on scalability and performance. ● Implement data validation and quality checks to maintain high data integrity across the BI platform. ● Conduct exploratory data analysis and provide actionable insights to guide product enhancements, user engagement strategies, and key decision-making processes. ● Stayup-to-date on BI tools, best practices, and trends to continuously improve the efficiency and capabilities of the BI platform. Requirement: ● 2-4years of experience in a BI Developer, BI Engineering, or Looker Admin role, ideally within a SaaS or tech environment. ● Proficiency in Looker, including dashboard creation, LookML, and data visualization, with a strong grasp of BI best practices and performance optimization. ● Background in computer science or a related technical field, with solid experience in SQL, data modeling, ETL processes, and handling large datasets. ● Experience in working with data warehousing and relational databases (e.g., PostgreSQL, MySQL), as well as integrating data from diverse sources. ● Familiarity with data pipeline tools and a willingness to contribute to ETL processes and data management. ● Ability to collaborate effectively with cross-functional teams, including engineering, data science, and product, to translate business needs into technical requirements. ● Strong analytical mindset, attention to detail, and adaptability to changing project priorities. ● Nice-to-have: Experience with cloud platforms (e.g., AWS, GCP, or Azure), Python for data manipulation, and familiarity with version control systems like Git.