AWS Data Engineer (6-10 yrs)

AWS Cloud Data Engineering for one of our client MNC

Location : remote

Job type : contractual for 1 yr + extendable

Exp : 5+ yrs

Key Responsibilities :

- Design, develop, and maintain scalable and efficient data pipelines on AWS.

- Implement data ingestion, transformation, and processing using AWS services such as Glue, Lambda, Kinesis, S3, and Step Functions.

- Work with Redshift, Athena, RDS, DynamoDB, and Snowflake to optimize data storage and retrieval.

- Develop and maintain ETL workflows using AWS Glue, Apache Spark, or Python.

- Ensure data integrity, security, and compliance following best practices.

- Implement and manage CI/CD pipelines for data engineering workloads.

- Collaborate with Data Scientists, Analysts, and Business teams to understand data requirements.

- Optimize performance and cost of data pipelines and cloud storage solutions.

- Monitor and troubleshoot data workflows using CloudWatch, AWS X-Ray, and logging frameworks.

Required Skills & Experience :

- 5-6 years of experience in AWS Cloud Data Engineering.

- Hands-on experience with AWS services like Glue, Redshift, S3, Lambda, Athena, Kinesis, and Step Functions.

- Strong programming skills in Python, PySpark, or SQL.

- Experience with data modeling, schema design, and query optimization.

- Familiarity with big data technologies such as Apache Spark, Hadoop, or Kafka.

- Knowledge of data security best practices (IAM roles, encryption, VPCs, etc.).

- Experience in Terraform or CloudFormation for Infrastructure as Code (IaC).

- Strong problem-solving skills with a focus on automation and scalability.

Preferred Qualifications :

AWS Certified Data Analytics - Specialty or Solutions Architect - Associate.