Data Engineer, AI – Cloud

🔥 2 minutes ago

🇨🇴 Colombia – 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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Keyrus

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1996

🤝 B2B

💼 Consulting

B2B • Data Analytics • Consulting

Keyrus is an international company passionate about leveraging data to make impactful changes in life, society, and the future. With a presence in 18 countries, Keyrus is dedicated to creating meaningful careers for its employees by fostering excellence, trust, creativity, kindness, and fun. Specializing in data analytics, data advisory, and management, Keyrus provides vendor-agnostic solutions and continuous training opportunities through its KLX platform. The company also emphasizes a healthy work-life balance with a range of benefits, including sports events, healthcare plans, and an inclusive work culture. Keyrus is committed to openness and transparency to maintain positive workplace relationships and is driven to innovate and influence the digital future.

📋 Description

• Design, build, and maintain production data pipelines, data models, and reusable data products supporting analytics, enterprise applications, and AI solutions • Develop and optimize ETL/ELT processes integrating structured and unstructured data from databases, APIs, files, and other enterprise sources • Implement data quality, testing, monitoring, lineage, and security practices • Prepare enterprise data for AI use cases, including RAG, retrieval systems, semantic context, and evaluation datasets • Manage and improve cloud-based data solutions for scalability, performance, reliability, and cost optimization • Collaborate with AI Engineers, Software Engineers, and Architects on reliable data integrations and reusable engineering solutions • Work with clients to understand business needs, address data challenges, and deliver solutions aligned with project goals

🎯 Requirements

• Hands-on experience designing, developing, and maintaining production data pipelines, data models, and ETL/ELT processes • Experience working with cloud data platforms and building scalable data solutions • Experience implementing data quality, testing, monitoring, and security practices in production environments • Understanding of data engineering best practices, including performance, reliability, maintainability, and version control • Strong communication skills, with the ability to explain technical ideas clearly, collaborate with stakeholders, and build relationships with clients and internal teams • Strong SQL skills, including complex queries, data modeling, transformations, and validation • Proficiency in Python or another programming language used for production data engineering • Hands-on experience with at least one major cloud data platform, such as Databricks, Snowflake, Microsoft Fabric, BigQuery, or Redshift • Experience with data processing, orchestration, and transformation technologies such as Spark, dbt, Airflow, or comparable tools • Knowledge of data ingestion, APIs, batch processing, and data integration patterns • Experience preparing structured and unstructured data for AI/GenAI applications, including RAG, embeddings, retrieval, and evaluation datasets is nice to have • Experience with vector databases, hybrid search, and maintaining retrieval indexes for AI applications is nice to have • Experience with streaming, change data capture (CDC), or event-driven data architectures is nice to have • Familiarity with semantic layers, knowledge graphs, feature stores, or MLOps integrations is nice to have • Experience with CI/CD, infrastructure automation, rapid prototyping, or BI dashboards is nice to have • Experience working directly with clients in consulting or professional services environments is nice to have

🏖️ Benefits

• 100% remote work • International and multicultural projects • Opportunities to work with leading technologies in Data, Cloud, and AI ecosystems • Access to training programs and continuous professional development • Professional growth opportunities and internal mobility • A culture built on collaboration, innovation, and continuous learning