Join a team driving enterprise data transformation through modern Lakehouse architectures, data governance frameworks, and cloud-native data platforms. As a Data Engineer Architect, you will lead the design and implementation of scalable, secure, and business-centric data ecosystems, enabling advanced analytics, AI/ML initiatives, and data-driven decision-making across the enterprise.

Your Role

You will be responsible for defining enterprise data architecture strategies, data governance frameworks, and up-to-date data platform roadmaps leveraging Databricks Lakehouse and cloud-native technologies. Working closely with business, analytics, AI/ML, and engineering teams, you will establish standards and best practices that ensure trusted, high-quality, and accessible enterprise data.

In this role, you will:

- Define and implement enterprise data architecture, governance frameworks, and target-state data platforms leveraging Databricks Lakehouse architecture
- Design and maintain conceptual, logical, and physical data models that support scalable, high-performance, and reusable data solutions.
- Establish and govern enterprise data policies covering data ownership, stewardship, metadata management, lineage, privacy, quality, and lifecycle management.
- Architect enterprise-scale data solutions using Databricks, Delta Lake, Unity Catalog, and cloud-native services across Azure, AWS, or GCP.
- Lead data modelling initiatives using dimensional modelling, Data Vault, canonical models, and normalized data structures
- Define and implement Master Data Management (MDM), reference data management, and enterprise data catalog capabilities.
- Establish data quality standards, monitoring frameworks, and remediation processes to ensure trusted and business-ready data.




- Drive metadata management and end-to-end data lineage capabilities using Databricks Unity Catalog, Microsoft Purview, Collibra, or similar platforms.
- Partner with Data Engineering, Analytics, and AI/ML teams to develop standardized data products and governed self-service analytics capabilities.
- Design secure and compliant data architectures incorporating access controls, data classification, encryption, masking, and regulatory requirements.
- Establish architecture standards for data ingestion, transformation, orchestration, and consumption using Databricks, Apache Spark, Delta Live Tables, and workflow automation frameworks
- Provide technical leadership and mentor architects, data engineers, and data stewards on enterprise data management best practices.

Your Profile

Mandatory Skills

- 14–17 years of experience in Data Architecture, Data Engineering, Data Governance, and Enterprise Data Modelling.
- Strong hands-on expertise with Databricks Lakehouse Platform, Delta Lake, Unity Catalog, Apache Spark, Delta Live Tables, Databricks Workflows, and MLflow.
- Experience designing and architecting enterprise-scale Lakehouse, Data Lake, Data Warehouse, Analytics, and AI/ML platforms.
- Strong expertise in Data Governance, Metadata Management, Data Quality, Data Lineage, Master Data Management (MDM), and Data Catalog solutions.
- Experience with Azure Databricks and Azure services including ADLS Gen2, Azure Data Factory, Microsoft Purview,



Azure Synapse, and Entra ID.
- Strong knowledge of enterprise data modelling techniques including dimensional modelling, Data Vault, canonical modelling, and normalized models.
- Proficiency with data architecture and governance tools such as ERwin, ER/Studio, PowerDesigner, Collibra, Alation, Informatica, Microsoft Purview, or equivalent solutions.
- Strong understanding of DAMA-DMBOK, TOGAF, and modern enterprise data management frameworks.
- Experience implementing secure, compliant, and scalable data management practices across enterprise environments.
- Strong stakeholder management, consulting, communication, and leadership skills.

Preferred Skills

- Experience supporting AI/ML, Data Science, and advanced analytics initiatives on enterprise data platforms. Knowledge of cloud-native data architectures across Azure, AWS, and GCP environments.
- Experience implementing enterprise-wide data governance and regulatory compliance programs.
- Exposure to modern data mesh, data fabric, and self-service analytics architectures.
- Relevant certifications in Databricks, Cloud Platforms, Enterprise Data Architecture, or TOGAF

. What You'll Love About Working Here

- Opportunity to architect enterprise-scale data platforms powering analytics, AI, and business transformation initiatives.
- Work with cutting-edge Databricks Lakehouse, Data Governance, and Cloud Data technologies.
- Collaborate with data architects, engineers, analytics teams, and business leaders on strategic transformation programs.
- Continuous learning through large-scale data modernization and innovation initiatives. [Job
- Flexible work environment that promotes technical excellence, leadership, and professional growth.

📌 Data Engineer Architect (Bangalore Urban)
🏢 Capgemini Engineering
📍 Bangalore Urban