About the role
? Level: Senior Associate /Manager Join a culture of high-performing innovators with endless ideas and a passion for tech. Our culture is the fabric of our company, and it is what makes us unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows everyone to be their best at Ascendion. Experience: 10-15 years overall, including 7+ years designing and implementing enterprise data governance and data management capabilities Lead, mentor, and scale a high-performing team of Data Engineers, BI Developers, and Analytics professionals. Define and execute the enterprise BI and Data Engineering roadmap aligned with organizational goals and digital transformation initiatives. Collaborate closely with business leaders, product owners, architects, and cross-functional stakeholders to drive data-driven decision-making. Own delivery governance, execution planning, resource allocation, and operational excellence across BI and Data Engineering initiatives. Drive KPI-based execution, engineering best practices, and continuous improvement initiatives. Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, or related disciplines. 8+ years of experience in Data Engineering, Business Intelligence, Analytics Engineering, and Enterprise Reporting. 4+ years of leadership experience managing enterprise engineering or analytics teams. Proven experience managing large-scale BI transformation and cloud analytics programs. Strong stakeholder management and customer-facing leadership experience. Architect and implement scalable, secure, and high-performance data platforms using Azure cloud technologies. Design and optimize enterprise data models supporting advanced analytics, self-service BI, and executive reporting. Build scalable data integration frameworks leveraging Azure Data Factory, Databricks, Synapse Analytics, SQL Server, and Data Lake technologies. Enable modern analytics architectures integrating Microsoft Fabric, Lakehouse patterns, and AI-driven analytics capabilities. Establish enterprise standards for data governance, metadata management, data quality, and security compliance. Ensure scalability, reliability, and performance optimization across enterprise BI and analytics platforms. Implement monitoring, observability, and audit frameworks for enterprise reporting and data engineering ecosystems. Drive best practices around role-based access control (RBAC), data lineage, compliance, and platform governance. Evaluate and adopt emerging technologies in Data Engineering, BI modernization, AI-driven analytics, and cloud ecosystems.