Data Engineer, AI

Job not on LinkedIn

🕒 July 3

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 30%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Cadastra

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2000

🛍️ eCommerce

📣 Marketing

☁️ SaaS

eCommerce • Marketing • SaaS

Cadastra is a leading digital performance and marketing solutions company in Latin America. They specialize in integrated strategies that combine marketing, technology, and data to help businesses grow exponentially. With over 25 years of experience, Cadastra empowers brands through services such as conversion optimization, media services, CRM and customer experience solutions, data analytics, and cloud services, catering to both B2C and B2B sectors.

📋 Description

• Propose and build: Design modern architectural solutions (focus on Data Lakehouse) and rapidly test new technologies. • Develop: Create efficient data processes and pipelines (ETL/ELT) using industry best practices. • Automate and Orchestrate: Implement automations in Cloud environments (GCP, AWS, or Azure), ensuring high performance, security, and data governance. • Operate with a Product Mindset: Ensure the data platform is scalable, flexible, and oriented to serve business areas with structured data and AI models. • Facilitate and Translate: Act as a bridge between technical and business teams, translating complex engineering and AI concepts for stakeholders in a clear and educational manner. • Collaborate: Support colleagues and teams in adopting industry best practices, serving as a technical reference.

🎯 Requirements

• Strong Python skills: Essential for developing Data Engineering and AI solutions. • Data Architecture: Solid experience with modern architectures, particularly Data Lakehouse. • Cloud Computing: Hands-on experience with cloud platforms (AWS, Azure, or GCP), focusing on managed data and AI services. • Orchestration and Pipelines: Experience with data orchestration tools (preferably Airflow). • Data Handling: Strong SQL skills and experience with ETL/ELT processes (data extraction via APIs, cleansing, deduplication, aggregation, and anonymization). • Best Practices: Experience with CI/CD (GitHub Actions / Cloud Build) and experience working in agile projects. • Autonomy and Proactivity (Builder): Hands-on, curious, and independent profile, able to propose solutions and validate hypotheses quickly. • Product Mindset: Ability to understand that the goal of engineering is not only the data but the product (data/AI) that addresses and solves other areas' needs. • Communication and Collaboration: Excellent communication skills to translate the "alphabet soup" of AI engineering for business teams, ensuring alignment and engagement.

🏖️ Benefits

• Meal and food allowance on FLASH card 🥗 • Home office stipend on FLASH card 💳 • Health insurance 🩺 • Dental insurance 🦷 • Birthday day off + an amount credited to the FLASH card 🎉 • Extended maternity and paternity leave 🍼 • Profit sharing (PLR) 💰 • Life insurance 🧡 • Childcare assistance 👶 • Referral bonus 💰 • Transport voucher 🚍 • Clude | Health platform 🩺 • TotalPass (fitness/wellness) 🏋🏽‍♀️