AI Data Engineer III

🕒 August 26

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

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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Rimini Street

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2005

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Rimini Street is a global leader in enterprise software support and services, providing end-to-end support solutions for mission-critical systems. The company specializes in reducing support costs, filling technology skills gaps, and providing strategic roadmap guidance to extend the life of ERP investments and enable business growth. With offerings that include managed and professional services, security solutions, interoperability, and compliance services, Rimini Street supports widely-used enterprise software such as Oracle, SAP, Salesforce, Microsoft, and more. By leveraging its extensive in-house engineering talent, Rimini Street offers clients unparalleled support, ensuring high satisfaction levels and cost savings.

📋 Description

• Build the knowledge layer of Rimini Street’s Agentic ERP Platform • Design and build RAG pipelines that retrieve relevant context for AI agent responses • Implement chunking, hybrid retrieval, query reformulation, retrieval evaluation, and reranking pipelines • Implement and manage vector storage with PostgreSQL and pgvector • Evaluate embedding models and build scalable embedding pipelines • Implement incremental indexing and multi-tenant vector architectures • Monitor and optimize vector search latency, accuracy, and resource utilization • Ingest knowledge from Salesforce, ServiceNow, documentation repositories, email archives, and ERP transaction logs • Build ETL processes to clean, normalize, and enrich raw data • Develop PDF extraction, HTML parsing, and structured data normalization pipelines • Build connectors to Salesforce, ServiceNow, SharePoint, and Confluence • Implement data quality monitoring, alerting, and lineage tracking • Design knowledge architecture across the Four-Spoke model • Build knowledge graphs, relationship models, and metadata taxonomies • Design knowledge versioning strategies and feedback loops for continuous improvement • Integrate with Snowflake and build pipelines between operational systems, Snowflake, and vector stores • Implement secure data access patterns respecting customer isolation • Design synchronization between the cloud data warehouse and real-time retrieval systems • Optimize query patterns for cost-effective processing at scale • Report to the Sr. Director, Engineering • Collaborate with GenAI Engineers and explain data architecture decisions to technical and non-technical stakeholders

🎯 Requirements

• 5+ years of data engineering experience • At least 1–2 years focused on AI/ML data pipelines or RAG systems • Hands-on experience building and optimizing RAG pipelines in production environments • Strong experience with vector databases, embeddings, and similarity search • Experience with ETL/ELT pipelines and data integration from diverse source systems • Production experience with PostgreSQL and SQL-based data processing • Background in Python for data processing and pipeline development • Python for data engineering: pandas, data processing pipelines, async programming • PostgreSQL with strong SQL skills, including JSONB, full-text search, and extensions • Experience with vector databases and embeddings, including pgvector or similar • Knowledge of RAG concepts: chunking strategies, embedding models, retrieval methods, and reranking • Experience with ETL/ELT patterns and orchestration tools such as Airflow, Dagster, or Prefect • Data modeling for relational and document-oriented use cases • Git version control and CI/CD practices for data pipelines • Understanding of REST or GraphQL API integration for data extraction • Fluent English, written and verbal • Bachelor’s or Master’s degree in Computer Science, Data Science, or related field desired • Experience with enterprise software companies or B2B SaaS platforms • Background in information retrieval, search systems, or NLP • Certifications in Snowflake, AWS Data Engineering, or similar • Contributions to open source data or AI/ML projects

🏖️ Benefits

• Compensation, bonuses, and benefits to match the skills of top-performing team members • Minimal travel; occasional travel for team meetings or training • Remote work environment • Diverse and inclusive environment • Equal Employment Opportunity • Rimini Street Foundation community and philanthropic initiatives