AWS Data Engineer

We are seeking an experienced AWS Data Engineer with 5-8 years of experience in designing, developing, and maintaining scalable data pipelines and cloud-based data solutions on AWS. The ideal candidate should have strong expertise in AWS data services, PySpark, SQL, ETL development, and modern data warehousing technologies.

Responsibilities

A day in the life

of an Infoscion • As part of the Infosys delivery team, your primary role would be to interface with the client for quality assurance, issue resolution and ensuring high customer satisfaction. • You will understand requirements, create and review designs, validate the architecture and ensure high levels of service offerings to clients in the technology domain. • You will participate in project estimation, provide inputs for solution delivery, conduct technical risk planning, perform code reviews and unit test plan reviews. • You will lead and guide your teams towards developing optimized high quality code deliverables, continual knowledge management and adherence to the organizational guidelines and processes. • You would be a key contributor to building efficient programs/ systems and if you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you! If you think you fit right in to help our clients navigate their next in their digital transformation journey, this is the place for you!

Requirements

Roles & Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines on AWS. Build and optimize data ingestion, transformation, and processing frameworks. Develop data solutions using AWS Glue, EMR, Redshift, S3, Athena, and Lambda. Create and optimize PySpark/Spark jobs for large-scale data processing. Design and implement data models, data warehouses, and data lakes. Work with structured and unstructured data from multiple sources. Ensure data quality, governance, security, and compliance standards. Implement workflow orchestration using Airflow or AWS Step Functions. Monitor and troubleshoot data pipelines and performance bottlenecks. Collaborate with Data Scientists, Analysts, and Business teams to deliver data solutions. Optimize cloud infrastructure costs and improve system performance. Participate in code reviews and follow DevOps best practices. Technical Requirements

Must Have:

5-8 years of Data Engineering experience. Strong AWS experience with: AWS Glue AWS EMR AWS Redshift AWS Athena AWS S3 AWS Lambda AWS IAM Strong expertise in PySpark and Apache Spark. Advanced SQL skills. Hands-on experience in ETL/ELT development. Experience with Data Warehousing and Data Modeling. Knowledge of Airflow or AWS Step Functions. Strong Python programming skills. Experience with Git and CI/CD processes.

Additional: Good to Have:

Databricks Snowflake Kafka/Kinesis Terraform Docker and Kubernetes Jenkins Delta Lake