Data Engineer AWS | Python, SQL, Redshift & Data Lake

Infosys Limited; São Paulo; Hybrid; BRL 180,000 - 280,000; Full time

Benefits offered by this job

Life insurance

Funeral assistance

Medical insurance

International projects

Global client exposure

International career mobility

Job summary

Infosys Brazil is seeking a Senior AWS Data Engineer to design, build and optimize scalable data pipelines in AWS, leveraging S3, Redshift and Lambda to serve analytics and reporting.

You will work with REST APIs, data modeling, and medallion architecture across data lake and warehouse layers, collaborating with global teams while delivering reliable data solutions for enterprise clients.

Qualifications

• Strong experience in data engineering within AWS environments.
• Proficiency with Python for data processing and automation.
• Advanced SQL and data warehouse concepts.
• Experience with REST APIs and JSON data sources.
• Knowledge of data modeling and Medallion Architecture.
• Ability to work with cross-functional teams and clients.

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.

Skills

Python

SQL

AWS Data Engineering

ETL/ELT

Data Modeling

REST APIs

Data Warehousing

Medallion Architecture

English Communication

Client Interaction

Tools

Amazon S3

Amazon Redshift

AWS Lambda

AWS Step Functions

AWS Glue

Amazon Athena

Amazon EMR

Kafka

Kinesis

Terraform

CloudFormation

Job description

Others (Please specify in the Requisition notes)

Domain

Delivery

Interest Group

Company

INFOSYS TECNOLOGIA DO BR

Requisition ID

154579BR

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

Preferred Qualifications

• 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.

Employment Type

• Life insurance.
• Funeral assistance.
• Medical insurance.
• Exposure to both national and international projects.
• Opportunity to work with global clients and multicultural teams.
• Potential for international career mobility within Infosys.

Language Requirements

• Advanced English proficiency for collaboration with international stakeholders and global teams.

Additional Required Qualifications

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About Us
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
EEO
Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.