AI Data Engineering and Sr Cloud Specialist

On-siteSeniorData Engineerposted 1mo ago

✦Role summaryAI-generated

Senior-level AI data engineer specializing in designing scalable cloud-native pipelines for autonomous driving data (sensors, simulations) with a focus on governance, optimization, and mentorship in Bengaluru.

About this role

Responsibilities:

Design, develop, and maintain scalable and efficient data pipelines and infrastructure to support autonomous driving research and development.
Extract, transform, and load (ETL) data from various sources, including sensors, simulations, and databases.Collaborate with data scientists, researchers, and engineers to understand data requirements and translate them into technical solutions.
Develop and optimize data storage and retrieval strategies, ensuring data quality and integrity.
Implement data governance and security measures to protect sensitive data.
Monitor and troubleshoot data pipelines and systems to identify and resolve issues promptly.
Continuously explore and evaluate new data technologies and tools to improve data processing efficiency and scalability.
Mentor and guide junior data engineers in their professional development.

Mandatory Core Skills & Competencies:

Strong proficiency in Python or another programming language commonly used in data engineering.
Expertise in data engineering tools and frameworks, such as Apache Spark, Hadoop, Kafka, and Airflow.
Deep understanding of data warehousing and data lake concepts.
Experience with cloud platform (Azure) and cloud-based data services.Knowledge of SQL and NoSQL databases.
Site Reliability Engineering.
Excellent problem-solving and analytical skills.
Ability to work independently and as part of a cross-functional team.Strong communication and documentation skills.

Nice to Have Skills:

Experience with machine learning and deep learning frameworks (TensorFlow, PyTorch).
Familiarity with autonomous driving technologies and concepts.Knowledge of data visualization tools (e.g., Tableau, Matplotlib).
Experience with real-time data processing and streaming technologies.
Understanding of data quality and validation techniques.Experience with containerization technologies (Docker, Kubernetes).
Familiarity with CI/CD pipelines and DevOps practices.
Experience with data governance and compliance frameworks (e.g., GDPR, CCPA).Ph.D. or Master's degree in Computer Science, Data Engineering, or a related field.Publications in relevant conferences or journals.