About The Opportunity
We operate in the Cloud Data & Analytics sector, designing and delivering AWS-native data platforms, ETL/ELT pipelines, and analytics solutions for enterprise clients across finance, retail, and SaaS industries. This role focuses on building scalable, secure data infrastructure on AWS to enable real-time insights and downstream BI/ML consumption.
Location: India (On-site). We are hiring an experienced AWS Data Engineer to own data platform components and operationalize production data workflows.
Role & Responsibilities
- Design, implement, and maintain AWS-native data pipelines (ingest, transform, catalog) using services such as AWS Glue, Lambda, S3, and Redshift.
- Develop and optimize PySpark/Apache Spark jobs for batch and streaming ETL to meet SLAs and cost targets.
- Build and maintain orchestration workflows with Apache Airflow; automate deployments using CI/CD and Infrastructure as Code (Terraform/CloudFormation).
- Implement data quality, monitoring, and observability (logging, metrics, alerts) to ensure pipeline reliability and fast incident resolution.
- Collaborate with Data Scientists, BI teams, and product stakeholders to translate data requirements into robust, production-ready pipelines.
- Drive performance tuning and cost optimisation for storage, compute, and query workloads across S3, Redshift, and EMR.
Skills & Qualifications
Must-Have
- Proven experience building production ETL/ELT pipelines on AWS using AWS Glue and Amazon S3.
- Hands-on development with Apache Spark and PySpark for large-scale data processing.
- Strong SQL proficiency and experience with Amazon Redshift or similar MPP data warehouses.
- Operational knowledge of Apache Airflow for orchestration and AWS Lambda for event-driven tasks.
- Experience with Infrastructure as Code and CI/CD for data platforms (Terraform or CloudFormation).
- Solid understanding of data modelling, partitioning, and query performance tuning for cloud data lakes and warehouses.
Preferred
- Experience with AWS EMR, Athena, Glue Catalog, or Lake Formation.
- Familiarity with containerization and orchestration (Docker, Kubernetes) for data workloads.
- Exposure to data governance, metadata management, or cataloging tools.
Benefits & Culture Highlights
- Work on end-to-end AWS data platform projects with cross-functional engineering and analytics teams.
- Opportunity for technical leadership and ownership of production data systems.
- Fast-paced, delivery-focused environment that prioritises reliability, automation, and measurable business outcomes.
How to Apply: This is an on-site role based in India. If you are a hands-on AWS Data Engineer who thrives in building scalable data platforms and delivering measurable analytics outcomes, we encourage you to apply.
Skills: amazon redshift,aws lambda,apache spark,terraform,aws
