Senior Data Platform and Automation Engineer

BrazilRemoteFull-timesenior

EngineeringAutomation Engineer

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Platform and Automation Engineer based in Brazil.

Technical Tools

EngineeringAutomation Engineer

This role offers the opportunity to design and build secure, scalable data platforms and governance automation for complex enterprise environments.
You will combine strong data engineering, cloud platform, software development, and enterprise integration expertise to create reliable and reusable platform capabilities.
The position has a broad technical scope, spanning data governance, metadata, lineage, data quality, access controls, APIs, automation, and production operations.
You will work closely with domain experts, product managers, governance specialists, and engineers to turn technical requirements into robust platform services.
Your work will help establish secure, observable, and highly automated foundations for governed data and AI-enabled applications.
As a senior technical contributor, you will also influence architecture, mentor engineers, and promote engineering standards across teams.
The environment values autonomy, collaboration, continuous learning, and the ability to take ownership of production-quality solutions from architecture through operational support.

Architect and develop secure, scalable data platform and governance automation capabilities using reusable, configuration-driven patterns.
Build automated controls covering metadata, data ownership, lineage, data quality, access management, and policy enforcement.
Implement enterprise security capabilities including identity management, authorization, role-based access control, least-privilege principles, auditability, service accounts, and credential management.
Develop secure APIs, MCP tools, and integrations supporting enterprise and AI-enabled applications.
Design and maintain automated validation, testing, deployment, and monitoring processes across development and production environments.
Establish strong observability for platform health, data quality, governance policies, system failures, and operational performance.
Own production-quality code, automated tests, technical documentation, and operational guidance throughout the full software and data engineering lifecycle.
Collaborate with domain experts, product managers, governance teams, and engineers to translate technical controls and business requirements into reliable platform services.
Contribute to architecture decisions, technical standards, and continuous improvements across engineering teams.
Mentor other engineers and provide technical guidance to help strengthen engineering practices and delivery quality.
Support production environments and troubleshoot issues across architecture, development, deployment, and ongoing operations.

Requirements

~2 min read

Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related STEM field, or a Bachelor's degree combined with a Master's or higher qualification in STEM.
6+ years of experience in software engineering, data engineering, or equivalent demonstrated technical expertise.
6+ years of hands-on experience with Python, SQL, distributed processing, data modeling, and modern data engineering frameworks.
Strong experience with cloud data platforms and data governance capabilities, including data catalogs, metadata, lineage, data quality, and access controls.
Practical experience with Databricks, Unity Catalog, Data Lake, Apache Spark, or comparable technologies.
Experience implementing CI/CD pipelines, automated testing, environment separation, and production deployments.
Experience developing secure APIs, MCP servers, or tools for enterprise and AI-enabled applications.
Strong understanding of enterprise identity, RBAC, service accounts, secrets management, authorization, and least-privilege security.
Demonstrated full-lifecycle engineering experience covering architecture, development, deployment, production support, and operational improvement.
Experience with GitLab CI/CD or comparable tooling is a plus.
Knowledge of policy-as-code, infrastructure-as-code, and configuration-driven platform approaches is desirable.
Experience building data marketplaces, governance platforms, internal developer platforms, or similar enterprise capabilities is advantageous.
Familiarity with privacy, security, regulatory, and AI governance controls is beneficial, particularly in regulated or risk-sensitive environments.
Strong problem-solving, communication, collaboration, and mentoring skills, with the autonomy to operate effectively in a remote environment.