Job Title: Principal Data Engineer – Azure & BI Modernization • • • W2 Requirement Key Responsibilities: Data Engineering & Analytics Platform Development • Design, build, and maintain enterprise-scale data pipelines using Azure Data Factory (ADF). • Develop and optimize Azure SQL-based data warehouses, data marts, and complex transformation logic. • Architect and implement Power BI semantic models with DAX, Power Query (M), and dimensional modeling (star schema) best practices. • Ensure data pipelines are efficient, reliable, and meet performance and security standards. Legacy System Modernization & Data Transformation • Lead legacy system analysis, data profiling, cleansing, and transformation activities. • Collaborate with stakeholders to define and document legacy and future-state data requirements. • Develop and execute comprehensive data migration strategies and processes for operational and case management systems. • Coordinate data synchronization and bridging efforts to support phased implementation across new platforms. • Provide hands-on leadership to ensure data quality, integrity, and alignment to modernized systems. Leadership, Collaboration & Governance • Lead and mentor a team of developers and analysts in best practices for data integration and transformation. • Oversee resource planning, task allocation, and status reporting for data conversion activities. • Collaborate cross-functionally with business users, system integrators, architects, and data scientists. • Evaluate and enhance the existing data architecture, driving innovation and scalability. Required Skills and Experience: • 8+ years of progressive experience in Data Warehouse/Data Mart environments, with a focus on cloud-based solutions. • Advanced expertise with Azure Data Factory (ADF) and Azure SQL Server. • Proven ability to deliver enterprise-grade Power BI semantic models, including advanced DAX and Power Query transformations. • Demonstrated experience in legacy data migration, including strategy definition, mapping, cleansing, and execution. • Proficient in SQL and experienced with data modeling methodologies (e.g., Kimball, Inmon, Boyce-Codd). • Familiarity with other cloud and big data platforms such as Databricks, Snowflake, AWS, or GCP. • Strong understanding of data governance, security, and compliance principles. • Excellent problem-solving, debugging, and analytical skills, particularly within large and complex data ecosystems. • Proven ability to lead cross-functional teams and communicate effectively with both technical and non-technical stakeholders. Preferred Qualifications: • Experience implementing CI/CD pipelines and infrastructure-as-code in a data engineering context. • Exposure to DevOps practices for data operations and delivery. • Experience supporting phased data bridging and live system cutovers during system modernization efforts. • Knowledge of data cataloging, metadata management, and data lineage tools.