Technical Lead - Data Engineering

Responsibilities

• Lead the end-to-end lifecycle of complex Data and AI projects, translating business goals into actionable technical roadmaps.
• Design and implement Medallion Data Lake architectures on Azure to integrate structured and unstructured data.
• Act as a subject matter expert in PySpark and Databricks to optimize high-performance data pipelines and ETL/ELT patterns.
• Collaborate with Data Scientists to integrate machine learning models into production environments.
• Enforce strict data security, governance, and compliance standards across all data platforms.
• Guide cross-functional squads of engineers and scientists through technical roadblocks to foster a culture of excellence.

Requirements

• 10–15 years of experience in data engineering and technical leadership.
• Expert-level proficiency in PySpark, Databricks, Python, and SQL.
• Deep expertise in Azure services, including Azure Data Factory, Databricks, and Azure Storage.
• Mastery of Data Modeling, Data Warehousing, and Medallion (Bronze/Silver/Gold) architecture patterns.
• Hands-on experience with Snowflake, Azure Datalake, and Lakehouse (Delta Lake) technologies.
• Strong understanding of cloud computing and data ingestion frameworks.

Preferred Qualifications

• Proficiency in ML/DL frameworks and the full development-to-deployment lifecycle.
• Experience integrating AI/ML models with Spark-based data processing.
• Understanding of LLM frameworks and their integration with data storage.
• Proven track record of leading large-scale migrations to Azure-native data stacks.
• Prior experience in a lead or co-lead role for Data or AI product development.

About the Company

Michelin is a global leader in mobility, dedicated to creating a sustainable future through innovation in tires, materials, and services. We empower our teams to drive progress by blending technical excellence with a passion for continuous learning and excellence.