Product Data Manager

Role Description Data Product Manager 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 infrastructure. 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. 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 . Responsibilities oDefine the vision and roadmap for data products (e.g., data platforms, analytics tools, ML infrastructure). oIdentify high value opportunities by investigating the data landscape, pain points, and business needs. oAlign data product strategy with organizational priorities and long-term data architecture, in partnership with the Enterprise Architecture team and various interested parties. oConnect data capabilities to business outcomes and organize efforts to achieve the business outcomes. oAlign engineering, analytics, and business teams. Uses metrics to guide prioritization and product evolution. oLead the end-to-end lifecycle of data products: requirements, design, development, testing, launch, and iteration. oPartner with data engineers and data scientists to build scalable pipelines, models, and data services. Ensure data quality, governance, lineage, and documentation standards are met. oTranslate business logic into data transformations, metadata, and domain specific rules.Skilled in or adept at data architecture, modeling, and pipelines. oEnsures data products are reliable, governed, and scalable. Qualifications Desired 7+ years of experience in Data management, data analytics, data engineering, or related fields. Demonstrated Product leadership skills and ability to work in ambiguity. Strong understanding of data systems: pipelines, warehousing, modeling, metadata, governance. Proficiency collaborating with data Architecture, data engineering and data science teams. Ability to translate complex technical concepts into business-friendly language. Strong communication, prioritization, and stakeholder management skills. 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. #J-18808-Ljbffr AM Solutions and Consulting