AWS Data Engineer
Actively Reviewing the ApplicationsViraaj HR Solutions Private Limited
India, Bhubaneswar, Odisha
Full-Time
INR 8–30 LPA
Posted 2 months ago
•
Apply by May 2, 2026
Job Description
Primary title: AWS Data Engineer
A leader in Cloud & Big Data Analytics, operating in the enterprise data engineering and business intelligence sector. We build scalable, secure data platforms and real-time analytics solutions on AWS that power reporting, machine learning, and operational decisioning for enterprise clients. This role is fully on-site in India and delivers production-grade data pipelines and data-lake/warehouse architectures.
Role & Responsibilities
Must-Have
A leader in Cloud & Big Data Analytics, operating in the enterprise data engineering and business intelligence sector. We build scalable, secure data platforms and real-time analytics solutions on AWS that power reporting, machine learning, and operational decisioning for enterprise clients. This role is fully on-site in India and delivers production-grade data pipelines and data-lake/warehouse architectures.
Role & Responsibilities
- Design, build, and operate scalable ETL/ELT data pipelines on AWS to ingest, transform, and deliver high-quality data for analytics and ML.
- Implement and manage data lake and warehouse solutions using S3 and Redshift, including partitioning, vacuuming, and query optimisation for cost and performance.
- Develop PySpark/Apache Spark jobs and serverless functions (Glue, Lambda) and orchestrate workflows with Apache Airflow or AWS Step Functions.
- Automate infrastructure deployment with Terraform or CloudFormation and integrate data pipelines into CI/CD pipelines for reliable releases.
- Monitor pipeline health and performance using CloudWatch, logging, metrics and implement alerting and remediation strategies.
- Collaborate with data scientists, analysts, and stakeholders to define data contracts, enforce data quality, and productionize models and datasets.
Must-Have
- Proficiency with core AWS data services: S3, Glue, Redshift, Lambda, EMR, Kinesis
- Strong experience with Apache Spark and PySpark for large-scale transformations
- Advanced SQL and data modeling skills for analytics and reporting
- Experience with workflow orchestration using Apache Airflow or AWS Step Functions
- Infrastructure-as-code experience using Terraform or CloudFormation
- Production-grade Python development, testing, and CI/CD practices
- Familiarity with streaming architectures and Kafka or AWS Kinesis streaming patterns
- Experience with containerization and orchestration: Docker and Kubernetes
- AWS certifications such as AWS Certified Data Analytics or AWS Solutions Architect
- On-site role with exposure to enterprise-scale AWS data platforms and cross-functional teams.
- Learning-first culture with opportunities for certification and technical upskilling.
- Competitive compensation and career growth into data platform or engineering leadership.
- Workplace: On-site
- Keyword focus: AWS Data Engineer, ETL, PySpark, Redshift, AWS Glue, Data Lake, Apache Airflow, Terraform. Skills: aws lambda,kubernetes,glue,docker,git,apache spark,terraform,python,sql,aws
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