Data Product Engineer — Databricks Lakehouse MVPs

RiseMe; Plano (TX); On-site; USD 116,000 - 155,000; Full time

Job summary

NTT DATA seeks a Data Product Engineer (Databricks) in Plano, TX to lead data product standards and end-to-end MVP Data Products on Databricks. You will partner with stakeholders to deliver high-value data products, drive governance, and implement scalable data pipelines across cloud platforms.

Applicants should have 10+ years in data engineering/architecture, 4+ years with Databricks, and strong collaboration skills to guide architecture workshops and client discussions.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Data engineering

Databricks

Spark

Delta Lake

Unity Catalog

Cloud platforms

Data governance

Data mesh concepts

Communication

Mentorship

Tools

Databricks

Delta Lake

Unity Catalog

Spark

Job description

NTT DATA seeks a Data Product Engineer (Databricks) in Plano, TX to lead data product standards and end-to-end MVP Data Products on Databricks. You will partner with stakeholders to deliver high-value data products, drive governance, and implement scalable data pipelines across cloud platforms.

Applicants should have 10+ years in data engineering/architecture, 4+ years with Databricks, and strong collaboration skills to guide architecture workshops and client discussions.