[Hiring] Technology Analyst @Infosys

Role Description

Infosys Brazil is looking for professionals with a Senior AWS Data Engineer | Python, SQL, Redshift & Data Lake profile to join our team.

Qualifications

• Strong experience in Data Engineering within AWS environments.
• Hands-on experience with Amazon S3, Amazon Redshift, AWS Lambda, and AWS Step Functions.
• Proven expertise in designing, developing, and maintaining scalable ETL/ELT data pipelines.
• Strong proficiency in Python for data processing, automation, and application development.
• Advanced SQL skills and solid understanding of Data Warehouse concepts.
• Experience integrating data from REST APIs and JSON-based services.
• Strong knowledge of data modeling and analytical schema design.
• Experience working with Medallion Architecture (Bronze, Silver, and Gold layers).
• Advanced English communication skills, with the ability to collaborate effectively in a global environment.
• Ability to work independently and interact directly with clients and cross-functional teams.

Requirements

• Experience with AWS Glue, Amazon Athena, and Amazon EMR.
• Knowledge of data quality, monitoring, and observability tools.
• Experience with event-driven architectures.
• Hands-on experience with streaming data pipelines using Kafka or Amazon Kinesis.
• Knowledge of CI/CD practices for data workflows and data platforms.
• Experience with Infrastructure as Code (Terraform or AWS CloudFormation).
• Experience delivering enterprise Analytics and Data Lake solutions.

Roles and Responsibilities

• Design, develop, and optimize data pipelines within AWS environments.
• Build and maintain data ingestion processes from APIs and various internal and external data sources.
• Transform, process, and deliver data for analytical consumption using Amazon Redshift.
• Ensure data quality, integrity, availability, and governance across the entire data lifecycle.
• Develop monitoring, alerting, and error-handling mechanisms for data pipelines.
• Optimize storage, query performance, and processing efficiency across Data Lake and Data Warehouse platforms.
• Collaborate closely with Data Analysts, Data Scientists, Architects, and business stakeholders.
• Create and maintain technical documentation for data models, integrations, and pipeline processes.
• Lead technical discussions with clients and global teams, ensuring successful delivery of data solutions.

Benefits

• Transportation allowance.
• Meal voucher.
• Childcare assistance.
• Life insurance.
• Funeral assistance.
• Medical insurance.
• Dental insurance.