Z2_Azure Data Engineer DevOps

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, we are currently seeking a  Data Engineer with Dev Ops to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

• BI FSL 2.0 Transformation & Solution Architecture
• Lead the end-to-end architecture and execution of BI FSL 2.0 transformation from SAP BW/BW4
  
  HANA to ne Xtollo/Azure Databricks.
• Translate existing SAP BW data models, transformations, process chains, extractors, and reporting logic into scalable Databricks Lakehouse patterns.
• Define the target-state data architecture covering ingestion, bronze/silver/gold layers, semantic consumption, Power BI integration, and reusable data products.
• Design SAP-to-Azure extraction and integration patterns using relevant approaches such as ODP, SLT, BW Bridge, APIs, CDC, or custom ETL frameworks.
• Drive fit-gap analysis between existing SAP BW capabilities and future-state ne Xtollo architecture.
• Establish architecture standards, design principles, reusable engineering patterns, and governance guidelines for the transformation program.
• Collaborate with business stakeholders, SAP functional teams, platform teams, data engineers, Power BI teams, and program leadership to ensure aligned execution.

• Design, build, and optimize enterprise-scale data pipelines using Azure Databricks, PySpark, Delta Lake, Azure Data Factory, and ADLS Gen
  2.
• Implement CI/CD pipelines for notebooks, workflows, data pipelines, infrastructure, configuration, and deployment across development, test, and production environments.
• Automate infrastructure provisioning and environment setup using Infrastructure as Code, preferably Terraform or equivalent Azure-native tooling.
• Define release management, branching strategy, code review process, deployment gates, rollback approach, and environment promotion standards.
• Implement observability, monitoring, alerting, logging, data quality checks, reconciliation, and operational dashboards for production-grade data platforms.
• Embed Dev Sec Ops  practices including secure secret handling, service principals, managed identities, RBAC, Key Vault integration, policy compliance, and audit readiness.
• Troubleshoot migration defects, pipeline failures, data mismatches, performance bottlenecks, and production issues with structured root cause analysis.

• Provide technical leadership to data engineers, developers, analysts, and external partners throughout the migration lifecycle.
• Own architecture decisions and ensure alignment with enterprise cloud, security, data governance, and platform standards.
• Support roadmap planning, sprint execution, dependency management, technical risk mitigation, and delivery governance.
• Create solution documents, architecture decision records, migration playbooks, runbooks, and design review material for leadership and engineering teams.
• Act as a bridge between business outcomes and technical implementation, ensuring the platform enables reliable, faster, and future-ready analytics.

• Azure, Databricks & Lakehouse Architecture
• Azure Databricks and Databricks Workflows
• Delta Lake, Medallion Architecture, and Lakehouse design
• Azure Data Factory or equivalent orchestration tools
• Azure Data Lake Storage Gen2 and cloud object storage patterns
• Azure SQL Database, Synapse Serverless SQL, or Databricks SQL
• Unity Catalog, data lineage, access control, and data product governance
• Azure Key Vault, Managed Identity, Service Principals, and secure connectivity
• Power BI consumption patterns and semantic layer enablement
• SAP BW/BW4
  
  HANA…