Key Responsibilities:

As a Data Management Engineer, you will be a crucial player in our data-driven decision-making process. Your role will involve developing, optimizing, and maintaining our business intelligence solutions, enabling stakeholders to access and utilize data for informed decision-making.

•  Data Collaboration: Collaborate with business units to understand their data needs and provide solutions that drive insights.
• Architectural Development: Design, construct, and maintain data architectures that align with business requirements and support data-driven initiatives.
• Data Acquisition: Oversee data acquisition processes, ensuring the seamless flow of data from various sources into our data ecosystem.
• Programming and Tool Utilization: Utilize programming languages and tools to create efficient and scalable data pipelines.
• Data Acquisition and Integration: Collaborate with cross-functional teams to integrate and centralize data from various sources into our business intelligence platform.
• Data Transformation: Implement ETL processes to transform raw data into usable formats for reporting and analysis.
• Data Quality Assurance: Identify and implement strategies to improve data reliability, efficiency, and quality.
• Data Modeling: Develop and maintain data models to support efficient data storage and enhance retrieval for reporting and analytics.
• Data Tool Development: Create data tools to empower data scientists and analysts in their pursuit of innovative solutions.
• Data System Enhancement: Work with data and analytics experts to enhance the functionality of our data systems.
• Dashboard Development: Design, develop, and maintain interactive dashboards and reports using tools like Power BI.
• Report Development & Automation: Design and create interactive and visually appealing reports, dashboards, and data visualizations using tools like Power BI, Alteryx, or similar.
• Performance Monitoring Optimization: Continuously monitor and optimize the performance of business intelligence solutions.
• Ad Hoc Analysis: Perform ad hoc data analysis to answer specific business questions and uncover actionable insights.
• Data Governance: Ensure data governance best practices are followed in reporting and analytics initiatives.