• Implement a functional SSAS environment. • Building and re-designing a set of reports that need to transition to an analysis services environment. • Work with our customer’s technical team to identify initial requirements. • Apply tabular, relational, and multidimensional data modeling methodologies. • Transform raw data into meaningful business decisions and pre-aggregate data for optimal results. • Document logical and physical data models. • Document and update reporting environment data model. • Develop new reports based on customer requirements

• Build and own the Azure data platforms for client accounts, SQL Server, Databricks, pipelines end to end • Design maintainable data models and challenge unclear requirements • Simplify complex data problems for clients and teams • Focus on client impact and meaningful contributions

• Design and implement scalable data architecture and end-to-end ETL/ELT pipelines • Analyze diverse data sources and create high-quality, structured data layers • Lead large-scale data migrations to cloud-based platforms (Azure, AWS, GCP) • Optimize complex SQL queries and database performance • Collaborate with analysts, data scientists, and business stakeholders • Ensure data governance, quality, and regulatory compliance • Mentor junior engineers and promote engineering best practices

• Deploy and manage AI evaluation processes across our infrastructure. • Process and perform comprehensive data analysis to identify trends, inconsistencies, and opportunities for model enhancement. • Build and maintain scalable data pipelines. • Collaborate with cross-functional teams to embed security and compliance considerations into the development lifecycle. • Automate repetitive workflows and implement solutions to improve operational efficiency.