Lead Data Engineer Noida (India)

8+ years of experience in Data Engineering. 5+ years of hands-on experience with AWS data services. Robust proficiency in Python and/or Scala. Experience building ETL/ELT pipelines at scale. Robust SQL and data modeling expertise (OLAP, dimensional modeling, lakehouse). Hands-on experience with : o Spark / PySpark o Airflow or similar orchestration tools o REST APIs and microservices Experience using GitHub Copilot or similar AI-assisted development tools in enterprise environments. Solid understanding of IAM, encryption, networking, and cloud security best practices. Preferred Qualifications AWS Certifications (e.g., AWS Certified Solutions Architect, AWS Certified Data Analytics). Experience with streaming technologies (Kafka, Kinesis). Experience with containerization (Docker, Kubernetes). Knowledge of Delta Lake, Iceberg, or Hudi. Experience implementing data observability solutions. Leadership & Soft Skills Proven ability to lead engineering teams and drive architectural decisions. Robust stakeholder communication skills. Ability to balance delivery velocity with engineering excellence. Experience working in Agile/Scrum environments. Nice to Have Experience implementing cost governance and FinOps best practices on AWS. Exposure to AI/ML pipeline integration. Experience designing multi-account AWS architectures. Mandatory Competencies Data Science and Machine Learning - Data Science and Machine Learning - Python Cloud - AWS - AWS S3, S3 glacier, AWS EBS Beh - Communication Programming Language - Scala - Scala Big Data - Big Data - Pyspark Big Data - Big Data - SPARK Programming Language - Python - Apache Airflow Data Science and Machine Learning - Data Science and Machine Learning - Apache Spark Database - Database Programming - SQL Database - Oracle - Data Modelling Artificial Intelligence - AI Tools - GitHub Copilot Middleware - API Middleware - Microservices Agile - Agile - SCRUM 8+ years of experience in Data Engineering. 5+ years of hands-on experience with AWS data services. Robust proficiency in Python and/or Scala. Experience building ETL/ELT pipelines at scale. Robust SQL and data modeling expertise (OLAP, dimensional modeling, lakehouse). Hands-on experience with : o Spark / PySpark o Airflow or similar orchestration tools o REST APIs and microservices Experience using GitHub Copilot or similar AI-assisted development tools in enterprise environments. Solid understanding of IAM, encryption, networking, and cloud security best practices. Preferred Qualifications AWS Certifications (e.g., AWS Certified Solutions Architect, AWS Certified Data Analytics). Experience with streaming technologies (Kafka, Kinesis). Experience with containerization (Docker, Kubernetes). Knowledge of Delta Lake, Iceberg, or Hudi. Experience implementing data observability solutions. Leadership & Soft Skills Proven ability to lead engineering teams and drive architectural decisions. Robust stakeholder communication skills. Ability to balance delivery velocity with engineering excellence. Experience working in Agile/Scrum environments. Nice to Have Experience implementing cost governance and FinOps best practices on AWS. Exposure to AI/ML pipeline integration. Experience designing multi-account AWS architectures. Mandatory Competencies Data Science and Machine Learning - Data Science and Machine Learning - Python Cloud - AWS - AWS S3, S3 glacier, AWS EBS Beh - Communication Programming Language - Scala - Scala Big Data - Big Data - Pyspark Big Data - Big Data - SPARK Programming Language - Python - Apache Airflow Data Science and Machine Learning - Data Science and Machine Learning - Apache Spark Database - Database Programming - SQL Database - Oracle - Data Modelling Artificial Intelligence - AI Tools - GitHub Copilot Middleware - API Middleware - Microservices Agile - Agile - SCRUM