Senior Data Management Analyst

Senior Data Management Analyst

Our client seeks a Senior Data Management Analyst who will be responsible for supporting significant system changes to turn the organization's data into scalable, high value products--such as curated datasets, analytics platforms, and data infrastructures supporting the Whole Family approach. This role will lead efforts across data engineering, data science, and business strategy that help mature data practices and teams and drive organizational efforts to shift to new data lakes and data curation platforms from current legacy main frame systems.

At a high level, the resource will lead the strategy, roadmap, and execution of data efforts enabling better decision making, operational efficiency, and intelligent product experiences. Partnering closely with data engineering, data science, analytics, and business policy and administration, the Data Product Manager will facilitate and help drive the path towards trusted, reusable, governed, and consumable data assets across the enterprise.

This role requires strong analytical skills, deep understanding of data systems, and a strong aptitude in translating between technical teams and business understanding, throughout the product lifecycle.

Tasks

• Product Strategy & Vision
• Data Product Development
• Interested Parties Management
• Analytics, Insights & Measurement
• Governance, Compliance & Ethical Data Use
• Provide knowledge transfer

Knowledge, Skills and Abilities Required (Soft Skills):

• Demonstrated Product leadership skills and ability to work in ambiguity.
• Ability to translate complex technical concepts into business-friendly language.
• Strong communication, prioritization, and stakeholder management skills.

Skills Required

• 4-7 years of experience in Data management, data analytics, data engineering, or related fields.
• Strong understanding of data systems: pipelines, warehousing, modeling, metadata, governance.
• Proficiency collaborating with data Architecture, data engineering and data science teams.
• Experience with analytics tools (dbt, Looker, Tableau, Power BI, Google Analytics).
• Understanding of large organizational data sharing constraints and data sharing agreements.
• Experience with SQL, data lakes, data and data pipelines / ETL.
• Significant experience with Databricks.
• Familiarity with Java and Python.
• Background in building internal platforms or developer facing products.
• Experience in implementing modern data architectures at an organization.
• Experience in a highly regulated industry performing statistical analysis and reporting.