• Lead the design of scalable data solutions • Mentor talented engineers • Work on projects that truly make an impact • Build and optimize data pipelines that power forecasting and analytics platforms • Collaborate with product managers, front-end and back-end developers, and fellow data engineers • Ensure adherence to architectural standards • Coach junior team members • Maintain consistent coding standards across global engineering pods

• Realizar a ingestão de dados em **processos batch** para o **Data Warehouse em ambiente de nuvem (AWS);** • Desenvolver, manter e evoluir **pipelines de dados (ETL/ELT)**, garantindo validação, automação e confiabilidade das informações; • Atuar na **sustentação e monitoramento dos pipelines**, utilizando boas práticas de **DataOps/DevOps**, assegurando disponibilidade e performance; • Estruturar e otimizar camadas de dados em **Data Lake e Data Warehouse**, garantindo organização, escalabilidade e governança; • Implementar e acompanhar controles de **qualidade de dados (Data Quality)**, identificando e corrigindo inconsistências; • Trabalhar em parceria com times técnicos e de negócio para entendimento das demandas e resolução de problemas relacionados a dados; • Ser proativo na **análise de processos existentes**, apresentando propostas de melhorias contínuas, otimização de pipelines e soluções técnicas alinhadas aos desafios identificados.

Role Description Candidates MUST BE located in USA due to client's technical requirements. - Remote position - Must-Haves: Full fluency in Spanish language. Candidate must have full fluency in both English and Spanish language. - Full Time Remote position - Hours: 8am to 5pm PST Mon-Fri - MUST BE AVAILABLE PACIFIC TIME ZONE. Join Volga Partners, a dynamic U.S.-based company at the forefront of Artificial Intelligence (AI) and Machine Learning (ML), proudly partnering with leading technology giants and global multinational corporations. - Fully remote role – Work from the comfort of your home - Entry to mid-level opportunity – Gain hands-on experience in data evaluation and AI - Flexible training hours – Get the support you need to succeed - This current opening is for full time. - Work with cutting-edge technology – Contribute to improving AI and language models Responsibilities - Data Evaluation & Annotation: Label and categorize text and images, ensuring accuracy and quality - Platform Management: Work within the client’s universal language platform to manage and evaluate language-based data - Trend Analysis: Track and assess data, identifying insights to enhance project quality - Quality Assurance: Ensure accuracy by proofreading and maintaining high-quality outputs - Process Improvement: Provide insights and recommendations to improve data relevance and performance - Adaptability & Collaboration: Work in a fast-paced environment with shifting priorities while maintaining communication with your team Qualifications - Fluency in English & Spanish – Must have full professional proficiency in both written and spoken communication - Strong analytical skills – Ability to evaluate data logically and provide sound reasoning - Attention to detail – A sharp eye for spotting inconsistencies and ensuring high data accuracy - Time management skills – Ability to manage multiple tasks efficiently - Critical thinking & problem-solving – Ability to make data-driven decisions - Tech-savvy mindset – Comfortable navigating platforms and tools - Adaptability & teamwork – Willingness to collaborate and adjust to changing project needs Requirements - Work Authorization: Must have valid authorization to work in the U.S. - Background Check: Required for this role - Equipment: Must have a personal laptop or computer Benefits - 401(k) - Paid time off - Fully Remote Company Description W2 Hourly $15-$18 (includes benefits such as PTO, 401K, where applicable). Job Types: Full Time, Contract, W2 Pay: $15.00 - $18.00 per hour Language: SPANISH Required Work Location: Remote

• Lead data platform strategy and execution • Partner with the CDAO to shape overall data strategy and translate it into engineering roadmaps with clear owners, timelines, and outcomes • Own the Snowflake data lake end to end • Develop, maintain, and evolve the platform and its associated services — from ingestion to serving • Build governance that actually works • Drive cross-functional data initiatives