DataOps Engineer, Specialist I

Grupo Boticário

DataOps Engineer at Grupo Boticário developing data automation and cloud solutions. Collaborating on improving data platform efficiency and implementing CI/CD pipelines.

Posted 5/11/2026full-timeRemote • 🇧🇷 BrazilLeadWebsite

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformPythonTypeScript

About the role

Key responsibilities & impact

Develop automations for the data platform using infrastructure as code, ensuring durability, high performance and ease of use while maintaining governance and security;
Maintain the data layer and its services, ensuring they are observable, scalable and flexible to meet the platform’s demands;
Drive engineering team efficiency by developing and implementing frameworks, methods and standards that optimize team activities;
Mentor and develop colleagues in data engineering best practices to promote scalability and cloud automations, collaborating closely with all teams;
Translate business needs into viable, reusable technological solutions for the platform, fostering a data-driven culture;
Create and validate hypotheses, adapting quickly to changes in priorities or situations;
Work autonomously while consistently relying on and supporting the team;
Own the data platform by identifying and refining requirements for improvements, optimizations and technological changes;
Monitor platform availability, performance, capacity and usage patterns, proposing tactical or strategic changes as needed.

Requirements

What you’ll need

CI/CD & Data Automation: Advanced experience building and maintaining CI/CD pipelines (preferably GitHub Actions), with a focus on automated deployment of infrastructure and data pipelines.
Cloud: Experience in cloud computing, preferably Google Cloud Platform (GCP).
Backend Development: Proficiency in Python and TypeScript, with a strong track record of developing robust APIs and scalable services.
Distributed Architecture: Deep experience with microservices architecture and distributed systems patterns.
AI Ecosystem: Experience developing and integrating AI agents and implementing MCPs.
Data Engineering (Differential): Knowledge of Data Lakehouse architectures, data modeling and data pipelines.
Technical autonomy for decision-making, critical architectural vision and the ability to lead resolution of complex problems.

Benefits

Comp & perks

Health
Medical and dental plan
Medication assistance
Health allowance for family members
Free psychotherapy sessions
Telemedicine and second medical opinion
Free flu vaccination
Health care programs
Food
Meal voucher or local restaurant allowance (depending on work model)
Food allowance
Christmas food allowance
Well-being and quality of life
Gym and fitness studio plan
Home office allowance (hybrid and remote work models)
Pet health plan
Birthday day off
Up to 40% discount on our products
Employee membership (agreements and partnerships, multi-brand store, gyms via TotalPass, courses and more)
Travel and accommodation program
Family
Childcare assistance
Child nutrition credit
Babysitter assistance
School supplies assistance
Legal, psychological and social guidance
Support for atypical parents
Extended parental leave (180 days for mothers and 120 days for fathers)
Mobility for on-site work
Transportation voucher and parking (hybrid and on-site models)
Financial security
Life insurance
Support in the event of parents' death
Private pension
Payroll-deductible loans
Benefit packages are configured according to eligibility rules.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

CI/CDdata automationinfrastructure as codePythonTypeScriptmicroservices architecturedata Lakehouse architecturesdata modelingdata pipelinesAI agents

Soft Skills

mentoringcollaborationadaptabilityautonomyproblem-solvingleadershipcommunicationteam efficiencycritical thinkingdata-driven culture