Lead Data Engineer

• 8+ years of experience in Data Engineering.
• 5+ years of hands-on experience with AWS data services.
• Strong proficiency in Python and/or Scala.
• Experience building ETL/ELT pipelines at scale.
• Strong 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.
• Strong 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