Sr. Principal Engineer - Electronics

Responsibilities & Key Deliverables

Key Tasks and Deliverables:

• Define and implement a scalable, unified data platform architecture for real-time automotive data ingestion, processing, and storage aligned with organizational goals.


• Oversee end-to-end data integration from vehicle telemetry, IoT sensors, customer feedback, and service records into a centralized repository.


• Ensure high data quality through rigorous validation, cleansing, versioning, and governance processes to maintain a single source of truth.


• Establish and enforce data security and privacy compliance, managing controlled access and audit trails.


• Standardize data engineering tools, coding practices, and automation to enhance platform efficiency and maintainability.


• Lead and develop a high-performing data engineering team, fostering technical expertise in big data, cloud architecture, and IoT data management.


• Collaborate cross-functionally with analytics, system intelligence, and insight delivery teams to translate business requirements into robust data infrastructure solutions.

Critical Must-Have Deliverables:

• A fully operational, scalable data platform capable of handling high-volume, real-time automotive and customer data.


• Robust, automated data pipelines ensuring seamless, resilient data ingestion and integration.


• Comprehensive data governance framework ensuring data quality, security, and compliance.


• A skilled and motivated data engineering team aligned with evolving technology trends and organizational objectives.


• Documented and standardized data engineering practices and tooling across the platform.
  
  
  

  Good-to-Have Deliverables:

  
  
  
  
  • Implementation of advanced analytics enablement features such as real-time streaming analytics and predictive data models.
  
  
  • Continuous innovation initiatives introducing emerging technologies and methodologies in data engineering.
  
  
  • Cross-functional training programs to enhance data literacy and collaboration across business units.
  
  
  • Contributions to industry forums or publications showcasing the organization’s data engineering capabilities.
  
  
  
  

Experience

15-22 yrs.

Minimum 10 years of progressive experience in data engineering or related fields, with at least 5 years in a leadership role managing large-scale data platforms.

Industry Preferred

Automotive, IoT, Technology, or Data-Driven Product Development industries

Qualifications

General Requirements

Competencies and Skills: Functional Competencies:

• Expertise in data platform architecture, data lake/warehouse design, and pipeline development.


• Strong knowledge of data integration techniques, ETL/ELT processes, and real-time streaming data.


• Proficiency in data governance, quality assurance, and security best practices. Tools and Techniques Used:


• Advanced proficiency with big data tools (e.g., Apache Spark, Kafka), cloud services (AWS/Azure/GCP), and data orchestration frameworks.


• Experience with containerization, automation tools, and version control systems.
  
  Behavioral Competencies:


• Strategic thinking with a results-driven mindset.


• Strong leadership and team development capabilities.


• Excellent communication and stakeholder management skills.


• Adaptability and continuous learning orientation.

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