Data Product Engineer; Databricks

Req .

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, NTT DATA's Client is currently seeking a Data Product Engineer (Databricks) to join their team in Plano, Texas (US-TX), United States (US).

Day to Day

Job Duties:

(what this person will do on a daily/weekly basis)

• Lead the design and implementation of enterprise Data Product standards, architecture patterns, and engineering practices within the Databricks ecosystem.
• Partner with business stakeholders, Risk domain teams, Data Product Owners, and technology leadership to identify high-value data products that support critical business use cases and analytics outcomes.
• Define and implement reusable data product frameworks, reference architectures, governance controls, metadata standards, and quality requirements to accelerate enterprise adoption.
• Architect and build multiple end-to-end MVP Data Products in Databricks, including data ingestion, transformation, quality controls, metadata management, security, lineage, and consumption layers.
• Develop scalable data pipelines and Lakehouse solutions utilizing Databricks, Delta Lake, Unity Catalog, Spark, and cloud-native services.
• Collaborate with Data Engineers, Data Architects, Governance teams, and platform teams to establish delivery standards that support product-based data management and domain-oriented ownership.
• Design and implement data product templates, CI/CD patterns, operational monitoring, observability controls, and automated testing frameworks to support repeatable delivery.
• Evaluate existing data assets, business processes, and technology capabilities to identify opportunities for modernization and improved data product adoption.
• Create proof-of-value demonstrations and working MVP solutions that validate architecture decisions, demonstrate business value, and establish implementation patterns for future teams.
• Lead technical workshops, architecture reviews, and stakeholder discussions focused on data product design, data contracts, interoperability, discoverability, and consumption patterns.
• Provide technical leadership and mentorship to engineering teams while driving alignment between strategic business objectives and practical delivery execution.
• Support proposal development, solution architecture discussions, effort estimation, and client presentations related to enterprise Data Product and Databricks transformation initiatives.

• Minimum 10+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, or Enterprise Data Management.
• Minimum 5+ years of experience designing and implementing modern cloud-based data platforms and data products.
• Minimum 4+ years of hands-on Databricks experience, including Delta Lake, Unity Catalog, Workflows, MLflow, and lakehouse architecture patterns.
• Minimum 5+ years of experience designing scalable data architectures and distributed data processing solutions.
• Minimum 4+ years of experience building enterprise data pipelines using Spark, Python, SQL and cloud-native technologies.
• Minimum 3+ years of experience implementing Data Product operating models, Data Mesh concepts, domain-driven data ownership, or product-oriented data delivery approaches.
• Minimum 3+ years of experience delivering cloud-based solutions on Azure, AWS or Google Cloud Platform.
• Experience implementing data governance, metadata management, data quality frameworks, lineage, and security controls within modern data platforms.
• Experience designing reusable engineering standards, architecture patterns, and platform accelerators that support large-scale enterprise adoption.
• Experienc…