Senior Data Developer, AWS

🕒 May 15

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

CI&T

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1995

🤖 Artificial Intelligence

☁️ SaaS

💰 $5.5M Venture Round on 2014-04

Artificial Intelligence • Cloud Services • SaaS

CI&T is a global tech transformation specialist focusing on helping organizations navigate their technology journey. With services spanning from application modernization and cloud solutions to AI-driven data analytics and customer experience, CI&T empowers businesses to accelerate their growth and maximize operational efficiency. The company emphasizes digital product design, strategy consulting, and immersive experiences, ensuring a robust support system for enterprises in various industries.

📋 Description

• Design and build end-to-end data pipelines across the RAW, Silver, and Gold layers of the Medallion Architecture, ensuring reliability, performance, and maintainability at each stage • Architect data ingestion, transformation, standardization, and serving processes, structuring data flows from diverse and heterogeneous sources into a coherent analytical foundation • Model data for analytical consumption following Data Warehouse best practices, including Star Schema design and dimensional modeling suited for business intelligence and AI-readiness • Identify, evaluate, and consolidate new data sources relevant to agronomic business objectives, proactively engaging stakeholders to understand, obtain, and validate data availability and quality • Interact with business stakeholders and client leadership to translate domain requirements into data architecture decisions, challenging assumptions and proposing solutions grounded in technical evidence • Manipulate, optimize, and serve data in multiple formats — including Parquet, CSV, and geospatial datasets — tailored to the consumption needs of downstream AI applications and map-based visualizations • Manage and configure cloud infrastructure end-to-end, including storage, compute, access control, serverless functions, data cataloging, and event-driven processing on AWS • Own deployment and CI/CD practices for data pipelines — including repository management, branching strategy, test gates, and automated deploy workflows via GitLab • Support the creation of the data layer that will feed AI/ML applications, ensuring data quality, structure, and availability meet the requirements of machine learning workflows — without directly developing the models themselves • Operate as a proactive technical partner in a greenfield environment: question, propose, experiment, and iterate with the team rather than execute in isolation

🎯 Requirements

• English proficiency at B2 level or above — ability to explain technical flows, engage in discussions, ask clarifying questions, and collaborate effectively with international stakeholders (accent is not a barrier; communication clarity is required) • Solid hands-on experience with AWS, covering the full infrastructure spectrum: S3, IAM (permissions and security configuration), Redshift, Lambda (serverless use cases), and Glue (including Glue Catalog for metadata management); ability to evaluate trade-offs between services for different pipeline scenarios • Experience with Terraform or equivalent Infrastructure-as-Code (IaC) tooling, applied recurrently in real data engineering projects — not just theoretical knowledge • Proficiency with GitLab for source control, CI/CD pipeline configuration, deployment workflows, and test gate management — specifically GitLab, not just generic Git experience • Strong proficiency in SQL, including complex query writing, analytical transformations, and performance tuning for data warehouse environments • Strong proficiency in PySpark, applied to large-scale distributed data processing — including partitioning strategies (e.g., by day/month/year), volume handling (tens to hundreds of GB), and performance optimization • Experience with Databricks, used in the context of data engineering pipelines and lakehouse architectures, including migration and deployment scenarios • Analytical data modeling expertise, with solid knowledge of Star Schema and dimensional modeling applied to data warehousing and business intelligence environments • Hands-on experience with the Medallion Architecture (RAW / Silver / Gold layers), including manipulation and optimization of Parquet and CSV files • Experience integrating and consolidating data from multiple heterogeneous sources, ensuring consistency, traceability, and analytical readiness • Mindset suited for greenfield projects: proactive, solution-oriented, comfortable with ambiguity, and able to contribute to architectural decisions — not just execute predefined tasks

🏖️ Benefits

• Health and dental insurance • Meal and food allowance • Childcare assistance • Extended paternity leave • Partnerships with gyms and health & wellness professionals via Wellhub (Gympass) TotalPass • Profit sharing and results participation (PLR) • Life insurance • Continuous learning platform (CI&T University) • Discount club • Free online platform dedicated to physical, mental, and overall well-being • Pregnancy and responsible parenting course • Partnerships with online learning platforms • Language learning platform