Mahindra and Mahindra Limited [Automotive and Farm Equipment Business]
Website:
mahindracareers.com
Job details:
1️. 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.
2️. 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.
3️. 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.
4️. Critical Experience Required:
- Minimum 15 years of progressive experience in data engineering or related fields, with at least 5 years in a leadership role managing large-scale data platforms.
- Preferred Industry:
- Automotive, IoT, Technology, or Data-Driven Product Development industries.
- Qualifications Required:
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or related technical discipline.
- Proven expertise in big data technologies, cloud platforms (e.g., AWS, Azure, GCP), and real-time data processing frameworks.
- 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.
Click on Apply to know more.