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Salary
≈ $27k – $63k per year (Estimated)
Location
Hybrid (Bengaluru, India)
Seniority
Staff · 10+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Oct 8, 2026. NTT DATA scores B on the Alion truth index.

Overview
Company
Impact
Profile match
NTT DATA is a Tokyo system integrator founded in 1988 that spun out of the data communications arm of NTT. It is one of the largest information technology services firms in the world, building banking, public sector and payment systems and operating global consulting and managed services. The company runs the CAFIS payment network used across Japanese retail and banking.

Req ID: 388542

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, apply now.

We are currently seeking a Z2_Azure Data Engineer with DevOps to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

Key Responsibilities

BI FSL 2.0 Transformation & Solution Architecture

  • Lead the end-to-end architecture and execution of BI FSL 2.0 transformation from SAP BW/BW4HANA to neXtollo/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 neXtollo 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.

Azure Data Engineering, DevOps & Platform Engineering

  • Design, build, and optimize enterprise-scale data pipelines using Azure Databricks, PySpark, Delta Lake, Azure Data Factory, and ADLS Gen2.
  • 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 DevSecOps 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.

Leadership & Delivery Ownership

  • 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.

Required Technical Skills

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/BW4HANA Migration & Integration

  • Strong understanding of SAP BW/BW4HANA concepts, data models, InfoProviders, transformations, process chains, and reporting dependencies.
  • Experience translating SAP BW logic into modern cloud data engineering patterns on Databricks.
  • Knowledge of SAP data extraction approaches such as ODP, SLT, CDS Views, RFC/API-based extraction, BW Bridge, or third-party replication tools.
  • Ability to assess migration complexity, data lineage, reconciliation needs, and functional equivalence between legacy and target platforms.
  • Exposure to SAP functional domains in logistics, supply chain, warehouse, transportation, or aftersales analytics is highly preferred.

Data Technologies

  • Python
  • PySpark
  • SQL/T-SQL
  • Spark
  • Delta Lake
  • Data Modeling
  • ETL/ELT Design
  • Data Warehousing Concepts
  • Performance Tuning

DevOps & Automation

  • Azure DevOps, GitHub, or Git-based enterprise source control
  • CI/CD pipeline design using YAML pipelines, GitHub Actions, or Azure DevOps pipelines
  • Infrastructure as Code using Terraform, Bicep, ARM templates, or equivalent tooling
  • Release management, environment promotion, approval gates, and rollback strategy
  • Automated testing for data pipelines, data quality validation, and reconciliation frameworks
  • DevSecOps controls for secrets, identity, policy, compliance, and audit traceability

Monitoring & Security

  • Azure Monitor
  • Log Analytics
  • Application Insights
  • Azure RBAC
  • Azure Policy
  • Key Vault Integration

Preferred Skills

  • Experience with large-scale SAP BW, data warehouse, or BI platform modernization programs.
  • Hands-on experience with Databricks Unity Catalog, Delta Sharing, Lakehouse Federation, or data marketplace patterns.
  • Experience with near real-time streaming, Kafka, event-driven architecture, or CDC pipelines.
  • Exposure to SAP Business Data Cloud, SAP Datasphere, or SAP Databricks concepts.
  • Experience with Agile/Scrum delivery, PI planning, roadmap execution, and multi-vendor collaboration.
  • Ability to work in a hybrid global team setup across India, Germany, platform teams, and business stakeholders.

Qualifications

  • 10+ years of experience in data engineering, data architecture, BI modernization, or enterprise data platform delivery.
  • Minimum 5+ years of hands-on experience with Microsoft Azure data services.
  • Minimum 4+ years of hands-on experience with Azure Databricks, PySpark, Delta Lake, and Lakehouse implementation.
  • Minimum 3+ years of practical DevOps experience for data platforms, including CI/CD and Infrastructure as Code.
  • Proven experience delivering complex migration or modernization programs from legacy data warehouses to cloud-native platforms.
  • Strong ability to lead architecture discussions, guide engineering teams, and influence senior stakeholders.

Certifications (Preferred)

  • Microsoft Certified: Azure Data Engineer Associate
  • Microsoft Certified: Azure DevOps Engineer Expert
  • Microsoft Certified: Azure Solutions Architect Expert
  • Databricks Certified Data Engineer Associate or Professional

Success Criteria for This Role

  • A clear and approved target architecture for BI FSL 2.0 on neXtollo/Azure Databricks.
  • Reusable migration patterns for SAP BW/BW4HANA objects, pipelines, data products, and Power BI consumption.
  • Automated and governed delivery process using CI/CD, IaC, monitoring, and DevSecOps controls.
  • Reliable data migration with strong reconciliation, performance, cost optimization, and production readiness.
  • Strong collaboration across business, SAP, cloud platform, data engineering, and reporting teams.

Soft Skills

  • Excellent communication and stakeholder management skills.
  • Strong analytical and problem-solving abilities.
  • Ability to work independently and lead technical initiatives.
  • Mentoring and knowledge-sharing mindset.
  • Strong documentation and presentation skills.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.

NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

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