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Data Engineer Jr+/Ssr – Gobierno de Datos en Azure
Data Engineer Jr+/Ssr to implement data governance in Azure, focusing on quality, cleansing, ETL/ELT, and validation with SQL, Python/PySpark, and Azure services.
Big Data Architect
Design end-to-end big-data architectures (Data Lakehouse, Data Mesh) and scalable ETL/ELT pipelines using Spark, Delta Lake, Iceberg, and cloud platforms (AWS/Azure/GCP).
AWS Glue Data Engineer
Designs and maintains AWS Glue-based ETL pipelines using Python and PySpark to integrate and process data across AWS services like S3, Redshift, and Lambda.
Home-Based DCX Data Engineer
Designs and maintains Snowflake-based ETL/ELT pipelines and dimensional data models to feed analytics and AI, ensuring high-quality, governed data for cross-functional teams.
Databricks Platform Engineer: Data Pipelines & Analytics
Designs and maintains scalable ETL/ELT pipelines on Databricks using Python and PySpark, ensuring data quality across cloud platforms like AWS, GCP, or Azure.
Full Stack Engineer (Python / Java / APIs)
Builds internal apps, APIs, and data pipelines in Java/Spring Boot and Python to operationalize AI across the business on AWS.
Solutions Architect (Enterprise Applications)
Designs enterprise application architectures, integrating APIs, ERP systems, and data flows while guiding teams on trade-offs and best practices, with a focus on automation and AI-assisted solution design.
Senior Data Engineer, 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…
Senior Data Engineer
Build and maintain Azure-based data pipelines and analytics models to power enterprise reporting and decision-making using Synapse, SQL, Python, and Power BI.
Cloud Data Engineer | Fabric, Databricks
Builds and optimizes a cloud lakehouse/data platform using Azure, Databricks, and Microsoft Fabric, designing scalable ETL/ELT pipelines and data models for analytics.
Senior Data & AI Engineer / MLOps Engineer – Productivización de Soluciones de IA
Senior Data & AI Engineer to industrialize ML models and AI solutions, designing ETL pipelines and deploying them in production using Python, PySpark, AWS, Docker, and Kubernetes.
DATA ENGINEERING
Build and maintain scalable, secure data pipelines and cloud infrastructure (AWS, Snowflake) to feed analytics and ML models, ensuring data quality and governance.
Data Engineer
Build and maintain AWS-based big-data pipelines using PySpark, Kafka, and Spark Streaming to process and transform large datasets in real time.
Senior Data & AI Engineer (Full-Stack DNA Specialist)
Senior engineer leading full-stack AI and data projects, from data architecture and MLOps to GenAI/LLM deployment and prompt engineering in production environments.
Senior Data Engineer - Azure Databricks
Build and maintain scalable data pipelines using Azure Databricks, DBT, Snowflake, and Python to migrate and process enterprise datasets.
Data Product Owner
The Data Product Owner defines and executes the vision, roadmap, and delivery of data products, bridging business, data, and tech teams to ensure scalable, high-impact solutions. Core focus: SQL, ETL/ELT, APIs, and cloud platforms with Agile/Scrum product management.
Senior Software Engineer II - Data Onboarding & Reporting
Build and scale Trino/Iceberg-based data pipelines for Wise’s finance team, transforming raw financial events into audit-ready reports using Medallion Architecture and Kafka.
Head of Integration, Data & GenAI Engineering
Lead AJ Bell’s integration, data and GenAI engineering teams to build secure, scalable platforms and AI solutions that align with business goals and regulatory needs.
Senior Data & AI Engineer - Hybrid (London) – LLMs, RAG, Azure, Databricks
Build and deploy production-grade AI systems, including LLM and RAG applications, on Azure and Databricks for a professional services firm.
Senior Data Engineer
Build and maintain scalable data pipelines in Databricks, design semantic models, and transform raw data into trusted datasets for analytics and reporting in a climate-focused domain.