Data Engineer, AI – Cloud

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Design, construct, and sustain production data pipelines, data models, and reusable data products that support analytics, enterprise applications, and AI solutions.

• Develop and enhance ETL/ELT processes that incorporate structured and unstructured data from databases, APIs, files, and other enterprise sources.

• Enforce data quality, testing, monitoring, lineage, and security practices.

• Prepare enterprise data for AI applications, including RAG, retrieval systems, semantic context, and evaluation datasets.

• Oversee and optimize cloud-based data solutions for scalability, performance, reliability, and cost-effectiveness.

• Collaborate with AI Engineers, Software Engineers, and Architects to ensure reliable data integrations and reusable engineering solutions.

• Engage with clients to comprehend business requirements, tackle data challenges, and implement solutions that align with project objectives.

⛳️ Requirements

• Practical experience in designing, developing, and maintaining production data pipelines, data models, and ETL/ELT processes.

• Experience with cloud data platforms and constructing scalable data solutions.

• Proven background in implementing data quality, testing, monitoring, and security practices in production settings.

• Solid understanding of data engineering best practices, including performance, reliability, maintainability, and version control.

• Excellent communication skills, with the capability to articulate technical concepts clearly, collaborate with stakeholders, and foster relationships with clients and internal teams.

• Strong SQL proficiency, encompassing complex queries, data modeling, transformations, and validation.

• Familiarity with Python or another programming language utilized in production data engineering.

• Hands-on experience with at least one major cloud data platform, such as Databricks, Snowflake, Microsoft Fabric, BigQuery, or Redshift.

• Experience in data processing, orchestration, and transformation technologies such as Spark, dbt, Airflow, or similar tools.

• Knowledge of data ingestion, APIs, batch processing, and data integration patterns.

• Experience in preparing structured and unstructured data for AI/GenAI applications, including RAG, embeddings, retrieval, and evaluation datasets is a plus.

• Familiarity with vector databases, hybrid search, and maintaining retrieval indexes for AI applications is advantageous.

• Experience with streaming, change data capture (CDC), or event-driven data architectures is beneficial.

• Knowledge of semantic layers, knowledge graphs, feature stores, or MLOps integrations is a plus.

• Experience with CI/CD, infrastructure automation, rapid prototyping, or BI dashboards is advantageous.

• Experience working directly with clients in consulting or professional services environments is a plus.

🏝️ Benefits

• 100% remote work.

• International and multicultural projects.

• Opportunities to engage with cutting-edge technologies in Data, Cloud, and AI ecosystems.

• Access to training programs and ongoing professional development.

• Opportunities for professional growth and internal mobility.

• A culture centered on collaboration, innovation, and continuous learning.