AWS Data Engineer - ETL/Python/SQL (3-8 yrs)

Job Title : AWS Data Engineer.

Location : Hyderabad.

Job Type : Fulltime.

Job Summary :

We are seeking a skilled AWS Data Engineer to design, implement, and maintain scalable data pipelines and infrastructure on AWS.

The ideal candidate will have expertise in AWS cloud services, big data technologies, and data engineering best practices to support our data-driven initiatives.

Key Responsibilities :

- Design and develop robust ETL/ELT pipelines using AWS services such as AWS Glue, Lambda, and Step Functions.

- Build and optimize scalable data architectures leveraging AWS technologies such as S3, Redshift, DynamoDB, and RDS.

- Implement data ingestion, transformation, and processing workflows using Apache Spark, Python, or SQL.

- Ensure data integrity, security, and governance by implementing best practices in data management.

- Monitor and troubleshoot data pipelines to ensure high availability and performance.

- Collaborate with data scientists, analysts, and other stakeholders to support data needs.

- Automate infrastructure deployment and data processing workflows using IaC tools like Terraform or AWS CloudFormation.

Required Skills & Qualifications :

- Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.

- 3+ years of experience in data engineering with AWS cloud technologies.

- Strong proficiency in SQL, Python, or Scala for data processing.

- Hands-on experience with AWS services such as AWS Glue, Redshift, S3, Lambda, Athena, Kinesis, and EMR.

- Experience with big data processing frameworks like Apache Spark or Apache Flink.

- Knowledge of DevOps and CI/CD practices for data pipeline deployment.

- Familiarity with data governance, security, and compliance best practices.

- Experience with Infrastructure-as-Code (IaC) tools such as Terraform or CloudFormation.

Preferred Qualifications :

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

- Experience with real-time data streaming and event-driven architectures.

- Knowledge of data warehousing concepts and relational database optimization.

- Exposure to machine learning and AI-driven data processing.