[Job - 30415] Senior Data Developer, Brazil

At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.

With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.

We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.

• Design, build, and maintain robust ETL/ELT processes to ingest, transform, and deliver data across a modern Data Lake architecture

• Develop and optimize distributed data processing workflows using Python and PySpark to handle large-scale datasets efficiently

• Implement and refine partitioning strategies for data lake storage frameworks (such as Delta Lake or Apache Iceberg) to balance query performance with storage costs

• Write, optimize, and translate complex SQL queries involving CTEs, window functions, conditional expressions, and aggregations

• Migrate and modernize data pipelines from legacy RDBMS platforms to cloud-native analytics environments

• Leverage object-oriented programming principles to contribute to in-house libraries for code reusability and standardization

• Work confidently with AWS-native services including Glue (Jobs, Catalog, Triggers, Workflows), Athena, Redshift, S3, Lambda, EventBridge, and related data services

• Collaborate with infrastructure and DevOps teams to provision and manage data resources using Infrastructure as Code (IaC) tools such as CloudFormation, CDK, or Terraform

• Monitor data pipeline health and performance using CloudWatch and other observability tools, proactively addressing issues and improving reliability

• Ensure data integrity, consistency, and compliance across pipelines and storage layers

• Implement metric tracking and observability frameworks to provide transparency into data workflows and SLAs

• Support data catalog management and metadata governance practices

• Partner with data analysts, scientists, and business stakeholders to understand requirements and translate them into scalable technical solutions

• Contribute to technical documentation, code reviews, and knowledge sharing within the team

• Stay current with emerging data engineering practices, tools, and cloud-native innovations

• Solid experience working with ETL processes and data pipeline development with AWS

• Strong proficiency in Python as the primary programming language, with demonstrated experience writing and optimizing PySpark code for distributed data processing

• Thorough understanding of SQL, including complex queries (CTEs, window functions, aggregations, conditional expressions) and experience translating workloads from legacy RDBMS platforms

• Hands-on experience with AWS Glue (Jobs, Catalog, Triggers, Workflows), Athena, and Redshift

• Solid understanding of Data Lake architectures and partitioning strategies to optimize performance and cost

• Good understanding of object-oriented programming (OOP) principles and experience working with reusable code libraries

• Comfortable working with Git, Shell scripts, and Linux environments

• Familiarity with observability, monitoring, and metric tracking practices

• English Advanced/Fluent

• Experience with open table formats such as Delta Lake or Apache Iceberg

• Knowledge of TypeScript

• Practical experience with Infrastructure as Code (IaC) tools such as CloudFormation (preferred), CDK, or Terraform

• Familiarity with additional AWS services such as SageMaker AI, ECS, RDS, DynamoDB, IAM, or EventBridge

• Experience working with Pandas for data manipulation and analysis

• Exposure to machine learning workflows or AI-driven data initiatives