Prodege - Analytics Engineer I - SQL

Primary Objectives

• Elicit and translate business needs: Collaborate with stakeholders to understand their data and reporting requirements, translating them into actionable technical specifications.
• Transform data into insights: Assist with designing and developing clear dashboards and visualizations, effectively communicating key business metrics and trends.
• Ensure data integrity: Maintain and optimize data pipelines ensuring accurate and timely delivery of data to external systems.
• Cultivate data expertise and stewardship: Develop a strong understanding of our data strategy, actively participating in data governance initiatives and acting as a data steward to ensure data quality, accuracy, and responsible use.
• Qualifications - To perform this job successfully, an individual must be able to perform each job duty satisfactorily.
• The requirements listed below are representative of the knowledge, skill, and/or ability required.
• Reasonable accommodations may be made to enable individuals with disabilities to perform the essential :
• Require AI/ML exposure with actual work preparing data for ML, building models, or enabling AI workflows.
• SQL and database skills are essential.
• Snowflake/dbt experience is optional if they have strong SQL and database knowledge.
• Candidates should understand the difference between OLTP and OLAP databases.
• BI/dashboard experience is important but any modern tools is acceptable (Power BI/Tableau/Omni) if there is stakeholder-facing reporting and metric visualization experience.
• Visualize insights: Create and maintain dashboards and reports that effectively communicate key business metrics and trends.
• Maintain and enhance data feeds to external partners, ensuring accurate and timely synchronization of business information
• Data Ingestion: Ingest, transform, and integrate data from various partners
• Ad-hoc reporting: respond to data requests and perform exploratory analysis to support decision-making and identify opportunities.
• Champion data quality and integrity, ensuring compliance with data governance policies and best practices