Data Engineer

Responsibilities • Design, develop, and maintain efficient ETL/ELT processes to support enterprise reporting and analytics needs. • Consolidate and transform data from a variety of internal and external sources into business ready datasets. • Design table structures and ETL/ELT to build scalable performance data solutions. • Develop automated validation, reconciliation, and monitoring processes to ensure data integrity and accuracy. • Implement auditing, balancing, and control mechanisms within data workflows. • Perform data analysis, root cause investigations, and complex ad hoc reporting as needed. • Contribute to solution architecture discussions and help guide the design and implementation of enterprise data initiatives. • Collaborate with database administrators, data architects, and technical teams to resolve issues and improve system performance. • Collaborate with database administrators, data architects, and technical teams to resolve issues and improve system performance. • Support the development of reporting and analytics applications by ensuring appropriate data structures and source availability. • Promote adherence to data governance, metadata management, and quality assurance standards. • Helping transition BI dashboards (currently moving from IBM’s Cognos to Microsoft Power BI) and creating quality scorecards and data lineage. Requirements • 10+ years of Data Engineering and Business Intelligence experience. • Demonstrated experience designing and implementing enterprise ETL/ELT solutions. • Hands on Python, SQL, DBT, and related data integration tools. • Knowledge of CI/CD practices and software development lifecycle methodologies. • Experience utilizing Git-based source control platforms for collaborative development, code management, and peer review processes. • Proficiency with modern development environments and debugging tools. • Proficiency in using Visual Studio Code as a development environment, including debugging tool to streamline coding workflows. • Experience with Snowflake for scalable data warehousing, including designing and optimizing data pipelines and leveraging its features for performance and security. • Hands on experience distilling business requirements into data warehouse design artifacts such as Facts Qualifier Matrix (FQM), source to target maps and star/snowflake schema data models. • Understanding of BI dashboards (IBM Cognos, Microsoft Power BI); experience creating data quality scorecards and data lineage. • Extensive experience with agile teams. • Assist and mentor development team in design and development of BI solutions. • Create visual models to enable collective understanding of processes, data flow, and user interactions. • Reporting application support experience. • Experience architecting small, medium, and enterprise-scale solutions. • P&C Insurance background strongly preferred.