NTT DATA is seeking a skilled Data Product Engineer with expertise in Databricks to join our dynamic team. This role is ideal for individuals passionate about innovation and growth within a forward-thinking organization. You will play a key part in shaping our data product strategy and implementation.

As a Data Product Engineer, you will drive the adoption of enterprise data product standards and best practices within the Databricks ecosystem. Your role involves collaborating with diverse stakeholders to identify and build high-value data products that address critical business needs and analytical outcomes.

We are committed to accelerating client success and positively impacting society through responsible innovation. As a Global Top Employer with experts in over 50 countries, NTT DATA offers a robust ecosystem of innovation and is part of NTT Group, a global leader in R&D investment.

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 supporting critical business use cases.

Define and implement reusable data product frameworks, reference architectures, governance controls, and quality requirements.

Architect and build end-to-end Data Products in Databricks, covering ingestion, transformation, quality, metadata, security, lineage, and consumption.

Develop scalable data pipelines and Lakehouse solutions using Databricks, Delta Lake, Unity Catalog, Spark, and cloud-native services.

Collaborate with cross-functional teams to establish delivery standards for product-based data management and domain-oriented ownership.

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, 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, and SQL.

Experience implementing data governance, metadata management, data quality frameworks, lineage, and security controls.

Strong communication and consulting skills with the ability to lead architecture workshops and executive discussions.