Principal Data Engineer

Job Title: Principal Data Engineer

Experience: 12–18 Years
Location: Bengaluru
Notice Period: Immediate Joiner

Job Summary

We are seeking a highly accomplished Principal Data Engineer / Data Engineering Architect to lead the design and execution of enterprise-wide data architecture and engineering strategies. This strategic leadership role is responsible for defining engineering standards, driving cloud modernization initiatives, building AI-ready data platforms, and partnering with executive stakeholders to enable data-driven digital transformation.

The ideal candidate will possess deep expertise in enterprise data architecture, cloud-native platforms, distributed data processing, and modern data engineering practices. You will play a pivotal role in shaping the organizations long-term data strategy while mentoring engineering leaders and driving innovation across enterprise data ecosystems.

Key Responsibilities

• Define and execute the enterprise-wide data engineering and architecture strategy aligned with business objectives.
  

• Architect scalable, secure, and cloud-native data platforms on Azure and/or AWS.
  

• Lead large-scale cloud migration, data modernization, and digital transformation programs.
  

• Design and implement AI-ready Lakehouse architectures to support advanced analytics, machine learning, and AI initiatives.
  

• Establish enterprise data governance, metadata management, data quality, security, and compliance frameworks.
  

• Drive platform engineering, automation, Infrastructure as Code (IaC), CI/CD, and DataOps best practices.
  

• Define engineering standards, architectural principles, development frameworks, and governance models across multiple delivery teams.
  

• Provide technical leadership and mentorship to engineering managers, architects, and senior data engineers.
  

• Collaborate closely with CXOs, Enterprise Architects, Product Leaders, and business stakeholders to define strategic roadmaps and technology investments.
  

• Evaluate emerging technologies, cloud services, and modern data engineering tools to drive continuous innovation.
  

• Design scalable API and event-driven architectures for enterprise data integration.
  

• Ensure platform scalability, reliability, performance, security, and operational excellence across enterprise environments.
  

• Lead architecture reviews, technical governance, and solution validation for complex enterprise programs.
  

Required Qualifications

• Bachelors or Masters degree in Computer Science, Information Technology, Engineering, or a related discipline.
  

• 12+ years of progressive experience in Data Engineering, Data Architecture, or Enterprise Data Platform development.
  

• Proven experience designing and implementing enterprise-scale cloud data platforms.
  

• Extensive expertise in enterprise architecture, cloud migration, and modernization initiatives.
  

• Strong knowledge of Lakehouse architecture, distributed computing, and modern data ecosystems.
  

• Experience leading multiple engineering teams across complex, large-scale enterprise programs.
  

• Demonstrated success in establishing engineering governance, architectural standards, and technology roadmaps.
  

• Strong consulting mindset with the ability to influence business and technology decisions.
  

• Exceptional leadership, communication, presentation, and executive stakeholder management skills.
  

Preferred Qualifications

• Experience designing AI-ready data platforms supporting Generative AI, Machine Learning, and Advanced Analytics.
  

• Cloud certifications such as Microsoft Certified: Azure Solutions Architect Expert, Azure Data Engineer Associate, AWS Certified Solutions Architect, or equivalent.
  

• Experience with containerization technologies (Docker, Kubernetes) and microservices architecture.
  

• Knowledge of data mesh, data fabric, and modern enterprise data architecture patterns.
  

• Familiarity with regulatory compliance frameworks and enterprise security best practices.
  

• Required Technical Skills

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  • Expert programming skills in Python and Scala
    
  • Extensive experience with Apache Spark
    
  • Deep expertise in Databricks
    
  • Strong experience with Snowflake
    
  • Hands-on knowledge of Apache Kafka and event-driven data processing
    
  • Strong expertise in Microsoft Azure and/or Amazon Web Services (AWS)
    

  • Experience with:

  • Azure Synapse Analytics

  • Azure Data Lake Storage

  • Cloud-native Data Platforms

  • Enterprise Data Governance and Metadata Management
    
  • Data Security, Privacy, and Compliance frameworks
    
  • MLOps and AI/ML Data Platform architecture
    
  • API Architecture and enterprise integration patterns
    
  • Event-Driven Architecture and real-time data streaming
    
  • CI/CD, DevOps, DataOps, and Infrastructure as Code (Terraform or equivalent)