Senior Databricks Data Product Architect (Lakehouse)

NTT DATA, Inc.; Plano (TX); Hybrid; USD 116,000 - 155,000; Full time

Benefits offered by this job

Medical insurance

401k with company match

Paid time off

Job summary

NTT DATA is seeking a Data Product Engineer (Databricks) in Plano, TX to lead the design and implementation of enterprise data product standards within the Databricks ecosystem. You will partner with stakeholders to identify high-value data products, define reusable frameworks, and build MVP Data Products across ingestion, transformation, and governance layers.

The role requires extensive experience in data engineering, data architecture, and cloud-based data platforms.

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.
• 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.
• Experience engaging directly with business stakeholders to translate business requirements into scalable data product solutions.
• Strong communication and consulting skills with the ability to lead architecture workshops, executive discussions, and technical solution reviews.

Responsibilities

• Lead the design and implementation of enterprise Data Product standards, architecture patterns, and engineering practices within the Databricks ecosystem.
• Partner with business stakeholders and technology leadership to identify high-value data products for critical business use cases.
• Define and implement reusable data product frameworks, reference architectures, governance controls, metadata standards, and quality requirements.
• Architect and build multiple end-to-end MVP Data Products in Databricks including ingestion, transformation, quality controls, 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.
• Design and implement data product templates, CI/CD patterns, monitoring, observability controls, and automated testing frameworks.
• Evaluate existing data assets and processes to identify modernization opportunities and improved adoption.
• Create proof-of-value demonstrations and working MVPs to validate architecture decisions and business value.
• Lead architecture reviews and stakeholder discussions focused on data contracts, interoperability, and consumption patterns.

Skills

Databricks

Delta Lake

Unity Catalog

Spark

Python

SQL

Cloud platforms

Tools

Workflows

MLflow

Azure

AWS

Job description

NTT DATA is seeking a Data Product Engineer (Databricks) in Plano, TX to lead the design and implementation of enterprise data product standards within the Databricks ecosystem. You will partner with stakeholders to identify high-value data products, define reusable frameworks, and build MVP Data Products across ingestion, transformation, and governance layers.

The role requires extensive experience in data engineering, data architecture, and cloud-based data platforms.