• Plays a leadership role in the analysis, design, development, documentation, implementation and maintenance support of data management platforms for all areas of the Bank through the project life-cycle and across single or multiple systems. • Investigates and trains other staff on identification of program errors, definition of problems, debugging, unit testing and implementation of changes. • Trains junior staff in data engineering concepts, standards, and best practices. • Provides training, assistance, and guidance for maintenance support of existing Bank applications, data management and analytics platforms and related package products as directed. • Interfaces with other data engineering, and data science teams to implement bank initiatives. • Demonstrates technical leadership by staying abreast of emerging data engineering technologies and implementing industry best practices. • Lead developing data solutions, provide subject matter expertise utilizing SQL Server, .net and Microsoft Azure technology stack and other relevant technologies in coordination with Enterprise Architects. • Actively leads process improvement initiatives. • At times, may be responsible to lead process improvement initiatives. • Reports task progress to applicable stakeholders. • Performs other duties as assigned.

• Work closely with team members on analysis, design, development, documentation, implementation and support of data design and modeling needs throughout the SDLC. • Provide vision, direction and leadership to improve the Data Architecture of the client. • Work collaboratively with staff to provide architectural guidance and leadership in the design and implementation of all active projects. • Lead design and technical problem-solving meetings focusing on technologies, proof of concept activities, and models related to data management. • Maintain a clear understanding of client’s strategic initiatives and requirements for shared data assets to evaluate current and emerging technologies and industry trends. • Collect, analyze and manipulate complex information in order to summarize and present recommendations that impact business decisions.

• Design, implement, and maintain Azure Data Factory pipelines for ingestion, transformation, and orchestration of data workflows. • Consume and process data from various structured and unstructured internal and external data sources. • Build scalable data models to support reporting and analytics use cases. • Develop and maintain dashboards and reports using BI tools (e.g., Power BI, Tableau, or similar). • Identify, troubleshoot, and resolve current data issues, ensuring data accuracy, reliability, and performance. • Implement best practices for data governance, security, quality, and documentation. • Collaborate closely with data analysts, data scientists, engineers, and business stakeholders. • Optimize data processes for performance, cost-efficiency, and scalability. • Monitor, test, and validate the performance of data flows and pipelines.

• Define and work within our data governance practices, including a catalog/dictionary and management of data quality, so that users understand and can trust what they are reporting about • Manage lights-out data operations of our ETL/ELT pipelines ranging from streaming inputs to batch file loads, to support customer reporting, development, and operations • Untangle, normalize, synthesize as needed to permit joining and comparisons from disparate sources, and further analysis including ML processing • Wrangle internal and external data into and through the reporting pipeline and schema • Design and run the security aspects of reporting – we manage healthcare and payments data; a safety mindset is at the foundation of everything we do • Handle reporting requests from stakeholders within and external to the business; over time, move from adhoc to systematic • Support data analysts and other internal consumers of the data • Support and enable ML/AI workloads