Description

You will design and drive end-to-end ETL and data-integration solutions for network anomaly detection and diagnosis.

Responsibilities

• Architect scalable AWS ETL pipelines using S3, Glue, EMR, Kinesis, and Lambda to process large-scale network and firewall log data.
• Design data models and storage strategies optimized for anomaly detection and analytics.
• Lead exploratory data analysis (EDA) and proof-of-concept development using Python and Spark.
• Define coding standards, governance, and CI/CD practices for distributed onshore and offshore development teams.
• Mentor offshore engineers and review deliverables to ensure performance, quality, and security compliance.

Required Skills

• 10+ years of experience in Data Engineering or Data Architecture with hands-on ETL and pipeline design.
• Proven experience architecting large-scale AWS data solutions including S3, Glue, EMR, Kinesis, and Lambda.
• Deep expertise in Python and Spark.
• Experience with ETL pipeline architecture and exploratory data analysis.
• Experience integrating Splunk, BigPanda, or equivalent monitoring and alerting platforms.
• Ability to lead distributed teams in Agile environments.
• Bachelor’s or Master’s degree in Computer Science Engineering or a related technical field.

Preferred Skills

• AWS Certified Solutions Architect (Associate or Professional).
• Experience in Firewall Analytics, Telecom domains, or network telemetry.
• Familiarity with Scala and anomaly-detection frameworks.

Key Skills

Education

Any Graduate