Overview
Skills
Job Details
Key Responsibilities:
Stakeholder Engagement & Requirements Gathering: Collaborate with business stakeholders to elicit and document high-impact requirements, translating them into clear, actionable functional and technical specifications for data and analytics solutions.
Product Ownership & Roadmap Management: Define, prioritize, and manage product backlogs for data initiatives, ensuring alignment with strategic goals and customer needs.
Solution Design & Implementation Support: Lead the design of business and data workflows; act as a liaison between business and technical teams to ensure optimal solution architecture and delivery.
Data Strategy & Governance: Develop standards and best practices for data quality, data governance, and lifecycle management, ensuring compliance with internal policies and external regulations.
Data Analysis & Insights: Perform complex data analysis and design metrics or dashboards that provide actionable insights to support decision-making.
Quality Assurance & User Testing: Collaborate with QA teams to validate functional and data-related solutions; ensure that the delivered products meet user expectations and performance standards.
Documentation & Communication: Maintain comprehensive documentation of data flows, system interfaces, and business logic; effectively communicate technical concepts to non-technical stakeholders.
Qualifications:
Education & Experience
- Bachelor s degree in Computer Science, Information Systems, Business, or related field.
- 5+ years of experience in business systems analysis, data analysis, or product management roles within data-driven environments.
Technical Proficiency
- Strong SQL skills and familiarity with at least one programming language (Python, R, or Scala).
- Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and cloud-native data services.
- Proficient with data visualization tools like Tableau, Power BI, or Looker.
- Knowledge of Data Lakehouse concepts (e.g., Delta Lake, Snowflake) and big data frameworks (e.g., Apache Spark).
- Working knowledge of Databricks platform