- Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement.
- Designing and building data pipelines to automate data movement and processing.
- Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI.
- Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements.
- Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.
Tech Stack &
Requirements :
- Large-Scale Platform Engineering Experience using technologies like Java, Spring boot, Microservices architecture, REST APIs and Service-Oriented Architecture (SOA), Event-Driven Architecture.
- Ownership of strategic technology roadmaps and platform modernization initiatives.
- Track record of driving engineering excellence through DevSecOps, automation, reliability, and operational resilience.