Data Engineer
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Job Description
- Execute end‑to‑end Enterprise Business Intelligence and Data Engineering initiatives, including requirement analysis, BI specification development, data modeling, solution design, deployment, and post‑production support.
- Serve as a technical consultant and facilitator between cross‑functional teams, ensuring effective communication and alignment among business units, project teams, and technical stakeholders.
- Perform root‑cause analysis and drive timely resolution of production issues, ensuring minimal disruption to BI processes and data platforms.
- Support both pre‑production and production data infrastructure environments, ensuring stability, performance, and adherence to operational standards.
- Participate in planning, preparation, and execution of periodic software releases, ensuring smooth deployment of enhancements, patches, and new features.
- Collaborate closely with project teams, business stakeholders, and leadership, translating business needs into scalable and maintainable data solutions.
- Coordinate with internal and external partners, such as vendors, integration teams, and cloud service providers, to ensure seamless project delivery and system operations.
- Conduct detailed requirements analysis and documentation, ensuring clarity, completeness, and alignment with enterprise architecture guidelines.
- Execute assigned project tasks and deliverables, contributing to successful completion of work packages within scope, timeline, and quality expectations.
- Perform advanced data analysis, data profiling, and validation to support data modeling, quality assessments, and integration design.
- Support the program manager in planning, coordination, and delivery of the overall Enterprise Business Intelligence program, ensuring alignment with strategic objectives.
- Ensure adherence to enterprise quality standards, including coding best practices, documentation, testing, and data governance policies.
- Contribute to Master Data Management (MDM) initiatives, supporting data quality, standardization, and stewardship processes across the organization.