Padmi
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Capgemini Invent

digital transformation consulting · SAP S/4HANA implementation

Data Engineer Architect

BangalorePosted 1 month ago
Infrastructure And DatabasesSeniorFull Time
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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 modern 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.

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