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Technical Data Migration Product Owner
NTT DATA, Inc.
Remote, USA
Full-time
Senior · 7+ years experience
Remote
USD 80-90 hourly / hour
Discovered 1 weeks ago
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- Gather and document business requirements from stakeholders.
- Create source to target mapping for data integration projects.
- Develop mock-ups and prototypes to visualize solutions.
- Verify and validate developed solutions to ensure they meet business requirements.
- Facilitate hand-off of solutions to business users and provide necessary training and support.
- Act as the primary point of contact for business stakeholders, addressing challenges, clarifying expectations, and fostering a collaborative work environment.
- Ensure solutions align with project priorities, quality standards, and business needs.
- 7+ years of experience in Data Analytics, Business Intelligence, Data Engineering, Product Ownership, or Business Analysis.
- Strong understanding of data warehousing, dimensional modeling, ETL/ELT design, and analytics solutions.
- Advanced SQL skills with the ability to analyze complex datasets and validate business requirements.
- Experience creating source-to-target mappings, business requirements documents, user stories, acceptance criteria, and functional specifications.
- Experience working with Agile delivery teams and managing product backlogs.
- Strong stakeholder management skills with the ability to bridge business and technical teams.
- Experience with Power BI and modern analytics platforms.
- Experience supporting cloud-based data platforms such as Snowflake, Databricks, or Azure Synapse.
- Experience leading user acceptance testing, solution validation, and production readiness activities.
- Experience leading enterprise data modernization and cloud migration initiatives.
- Experience migrating data warehouses, ETL pipelines, reporting assets, and analytical workloads from on-premises platforms to cloud platforms.
- Experience with Snowflake, Databricks, Azure Data Factory, or similar cloud-native data technologies.
- Experience with data quality validation, reconciliation, migration testing, and cutover planning.
- Knowledge of data governance, metadata management, lineage, and regulatory requirements.
- Experience working in retail, supply chain, consumer products, or enterprise-scale analytics environments.
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