Top Data Engineer Jobs in Brasilia

Design and build scalable ETL/ELT data pipelines and a cloud-based data warehouse/lakehouse. Improve data quality, governance, and documentation. Work with stakeholders to enable analytics, BI, and machine learning by delivering clean, analytics-ready datasets and establishing data engineering best practices.

Build and maintain scalable ELT/ETL pipelines and data models for cloud cost attribution and financial reporting. Design a Cloud Economics data warehouse, perform end-to-end validation and auditing, automate cost-optimization recommendations, and deliver high-quality datasets for Product, Engineering, and Finance stakeholders.

Design, build, and maintain high-performance backend microservices and automation for the GTM Data Platform. Implement RESTful APIs, webhook-driven lead routing, and Salesforce integrations. Support AI-driven sales workflows, maintain platform codebase, and collaborate in Agile/Scrum using JIRA with distributed teams aligned to EST.

Build the data foundation and LLM analysis layer for a Creative Engine: ingest and structure multi-platform performance and sales data, run video analysis with Gemini and Claude, implement semantic search with pgvector, connect signals into a queryable intelligence layer, integrate platform APIs, and own full-stack features (Django + HTMX + Tailwind) with async pipelines (Celery + Redis).

Design, build, and maintain cloud data pipelines and Snowflake/dbt data models; develop AI-powered applications using LLMs, RAG, tool-calling, and agent workflows; create APIs and integrations; monitor performance, data quality, and costs; troubleshoot interconnected systems; apply security, governance, testing, and CI/CD best practices; partner with stakeholders to deliver scalable solutions.

Own and operate Databricks production data pipelines for a predictive CRM platform: monitor, optimize cost and performance, migrate legacy ETL, enforce Delta Lake and multi-tenant architectures, ensure data quality/security, support customer onboarding, and maintain runbooks and CI/CD for global, SLA-driven delivery.

The role involves designing and optimizing distributed data systems, building real-time data pipelines, and mentoring engineers while focusing on scalable data architecture and AI infrastructure.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.