Infosys—AWS Data Engineer

Job description

Description: Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines on AWS. Build and optimize data ingestion and transformation workflows. Develop and manage data lakes and data warehouse solutions. Work with large-scale structured and unstructured datasets. Implement data quality, governance, and security best practices. Optimize data processing performance and cost efficiency. Collaborate with business analysts, data scientists, and application teams. Monitor, troubleshoot, and resolve data pipeline issues. Support data migration and modernization initiatives. Create technical documentation and maintain data architectures. Required Skills AWS Glue AWS EMR Amazon Redshift Amazon S3 AWS Athena AWS Lambda SQL Python PySpark / Apache Spark ETL Development Data Warehousing Data Lake Architecture Good-to-Have Skills AWS Kinesis Apache Airflow Kafka Snowflake Databricks Terraform CI/CD Pipelines Hadoop Ecosystem Qualifications Bachelor's degree in Computer Science, Information Technology, or related field. 3-5 years of relevant Data Engineering experience. Experience working in cloud-based data platforms and analytics environments. Strong problem-solving and communication skills. Requirements: We are looking for an experienced AWS Data Engineer with 3-5 years of experience in designing, developing, and maintaining scalable data pipelines and cloud-based data solutions. The ideal candidate should have strong expertise in AWS data services, ETL development, and big data technologies. Responsibilities: Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines on AWS. Build and optimize data ingestion and transformation workflows. Develop and manage data lakes and data warehouse solutions. Work with large-scale structured and unstructured datasets. Implement data quality, governance, and security best practices. Optimize data processing performance and cost efficiency. Collaborate with business analysts, data scientists, and application teams. Monitor, troubleshoot, and resolve data pipeline issues. Support data migration and modernization initiatives. Create technical documentation and maintain data architectures. Required Skills AWS Glue AWS EMR Amazon Redshift Amazon S3 AWS Athena AWS Lambda SQL Python PySpark / Apache Spark ETL Development Data Warehousing Data Lake Architecture Good-to-Have Skills AWS Kinesis Apache Airflow Kafka Snowflake Databricks Terraform CI/CD Pipelines Hadoop Ecosystem Qualifications Bachelor's degree in Computer Science, Information Technology, or related field. 3-5 years of relevant Data Engineering experience. Experience working in cloud-based data platforms and analytics environments. Strong problem-solving and communication skills. Skills: Technology-AWS Glue, EMR, Redshift, Athena, S3, Lambda, Python, SQL, PySpark, Spark, ETL, Data Pipeline, Data Lake, Data Warehouse, Kinesis, Airflow, Databricks, AWS Data Engineer.