Software Engineer
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.
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.
As CI&T continues to expand its data and analytics capabilities, we are seeking a talented and experienced Data Developer to join our team and drive the evolution of modern data platforms for our clients. This role is critical in designing, building, and optimizing scalable data pipelines and lake architectures that empower data-driven decision-making across the organization.
The Data Developer will work with cloud-native solutions to support the entire data lifecycle—from ingestion and transformation to storage optimization and analytics enablement. This position requires strong technical expertise in distributed data processing, deep SQL proficiency, and a solid understanding of cloud infrastructure, particularly within the AWS ecosystem. The ideal candidate will balance performance, cost, and maintainability while contributing to reusable, well-architected data solutions.
Responsibilities:
Data Pipeline Development & Optimization:
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
Data Transformation & Modeling:
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
Cloud Infrastructure & Orchestration:
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
Data Governance & Quality:
Posted July 31, 2026