About the Role :
We are seeking a seasoned Data Engineering Architect with 15+ years of experience designing and scaling enterprise-grade data platforms to lead the architecture of our Connected Electric Vehicle (EV) Platform.
This role requires deep expertise in cloud-native (AWS & GCP) data ecosystems, real-time streaming infrastructure, and architecting solutions for high-velocity, high-volume telemetry generated by Electric Vehicle.
Skill Sets Required :
- 15+ years of experience in Data Architecture and Engineering
- Deep understanding of structured and unstructured data ecosystems
- Hands-on experience with ETL, ELT, stream processing, querying, and data modeling
- Proficiency in tools and languages such as Java, Spark, Kafka, Airflow, and Python
- Proficiency in SQL and MongoDB
- Proven experience in building and maintaining data warehouses and data lakes
- Experience in implementing data quality standards and performing exploratory data analysis (EDA)
- Experience with any public cloud platform : GCP, AWS, or Azure
- Strong knowledge of data governance, privacy, and compliance standards
- Expertise in designing high-performance and cost-optimized data engineering pipelines leveraging Medallion Architecture
- A strategic mindset with the ability to execute hands-on when needed
Good to Have :
Knowledge of GraphQL / Graph databasesExposure to connected vehicle platformsExperience in the EV or automotive domainKnowledge of API developmentExposure to data mesh and data fabric conceptsResponsibilities :
Design scalable, secure, and high-performance data architectures across cloud and on-premise environments for our connected vehicle platformLead the end-to-end architecture of data pipelines and real-time streaming solutions using Kafka, Kinesis, Google Pub / Sub, Apache Flink, or Dataflow.Establish best practices for tiered storage across hot, warm, and cold data using BigQuery, Redshift, S3 / GCS, and Delta Lake.Collaborate with cross-functional teams and business stakeholders to ensure data solutions meet analytical and operational requirementsEnable AI / ML readiness through clean, governed, and performant data pipelines for predictive models.Evaluate and recommend tools and technologies to improve the data platform by conducting proof of concepts (PoCs)Ensure compliance with data security, privacy, and regulatory standardsMentor and guide data engineers and solution architectsEstablish best practices and coding standards for data engineering teamsStay current with emerging technologies and drive adoption of modern data practicesLead and contribute to technical discussions and decision-makingQualifications :
Bachelor’s or Master’s degree in any discipline15+ years of industry experience, with a minimum of 10 years in data engineering