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

Infosys; Região Geográfica Intermediária de São Paulo; Sur place; BRL 180 000 - 300 000; Plein temps

Avantages offerts par ce poste

Transportation allowance

Meal voucher

Childcare assistance

Life insurance

Dental insurance

Medical insurance

Flexible working hours

Résumé du poste

Infosys Brazil is seeking a Senior AWS Data Engineer to join our team and design, develop, and optimize data pipelines in AWS. You will ingest data from APIs and various internal and external sources, transform data for analytics with Redshift, and ensure governance across the data lifecycle.

The role requires strong Python and SQL skills, Medallion Architecture knowledge, and the ability to collaborate with global teams. Flexible hours are offered in a multinational environment.

Qualifications

• Strong AWS data engineering experience and scalable pipeline design.
• Proficient in Python for data processing and automation.
• Advanced SQL and data warehousing concepts.
• Experience with REST APIs and JSON data sources.
• Knowledge of Medallion Architecture (Bronze/Silver/Gold).
• Excellent English communication for global collaboration.
• Ability to work independently with clients and cross-functional teams.

Responsabilités

• Design, develop, and optimize data pipelines in AWS.
• Build data ingestion from APIs and various data sources.
• Transform and deliver data using Amazon Redshift for analytics.
• Ensure data quality, governance, and lifecycle integrity.
• Develop monitoring, alerting, and error-handling for pipelines.
• Optimize storage, queries, and processing across Data Lake/ DW.
• Collaborate with analysts, scientists, architects, and stakeholders.
• Create documentation for data models, integrations, and pipelines.
• Lead technical discussions with clients and global teams.

Connaissances

Data Engineering

Python

SQL

Data modeling

Medallion Architecture

REST APIs/JSON

English communication

Independent work

Outils

Amazon S3

Amazon Redshift

AWS Lambda

AWS Step Functions

AWS Glue

Amazon Athena

Amazon EMR

Terraform or CloudFormation

Kafka or Kinesis

Description du poste

• Flexible working hours.

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.

Additional Information

Employment Type

• Full-time, permanent position (CLT).
• Flexible working hours.

Benefits

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

Career Opportunities

• 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.