Description

You will design and deliver cloud-native data solutions using AWS, Hadoop/Spark, and Kafka to build low-latency pipelines and real-time analytics engines.

This role is on-site.

Responsibilities

• Build enterprise data models and front-office workloads using AWS services including Lambda, S3, Glue, Athena, and CloudWatch.
• Drive engineering discipline through code reviews, automated validation, performance tuning, and enterprise-grade CI/CD practices.
• Ensure production readiness by managing resilience, monitoring, alerting, data integrity, and incident triage for RTB operations.
• Collaborate with global architects and stakeholders to convert conceptual designs into production-ready components and lead Agile delivery.
• Maintain secure coding standards and implement effective unit testing to ensure code reliability and readability.

Required Skills

• 14+ years of experience in software development and data engineering.
• Strong proficiency in AWS (Lambda, S3, Glue, Athena, CloudWatch) and Python.
• Experience with Hadoop/Spark and Kafka for event-driven architectures.
• Proven track record in low-latency engineering and performance tuning.
• Deep understanding of CI/CD practices and automated validation.
• Experience working in globally distributed environments.
• Ability to partner with senior stakeholders and lead end-to-end ownership of features.

Preferred Skills

• Exposure to Snowflake, Databricks, Java microservices, or Angular.
• Knowledge of AI/ML concepts such as RAG and agentic workflows.
• Data governance and data product experience.

Key Skills

Education

Any Graduate