Job Description
8+ years of experience in Data Engineering.
5+ years of hands-on experience with AWS data services.
Solid 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:
Spark / PySpark
Airflow or similar orchestration tools
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 settings.
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 AI - Data Engineering - Data Quality Validation
Data AI - Data Engineering - Apache Kafka
Data AI - ETL OTHERS - Snowflake
Big Data - Big Data - Pyspark
Data Science and Machine Learning - Data Science and Machine Learning - Apache Spark
Data Science and Machine Learning - Data Science and Machine Learning - Python
Data Science and Machine Learning - Data Science and Machine Learning - Databricks
Database - Database Programming - SQL
📌 Lead Data Engineer Uttar Pradesh
🏢 IRIS SOFTWARE
📍 Uttar Pradesh
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