Senior AI Data Engineer

Job not on LinkedIn

🔥 1 minute ago

🇨🇴 Colombia – Remote

💵 Col$6k - Col$7.5k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.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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Cadre AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

💼 Consulting

🤖 Artificial Intelligence

🤝 B2B

Consulting • Artificial Intelligence • B2B

Cadre AI is an AI strategy and implementation firm that helps companies identify high-impact AI opportunities, integrate AI into existing tech stacks, and deliver measurable business results such as revenue growth and improved EBITDA. They offer services across AI Strategy, AI Leadership & Facilitation (training/executive enablement), AI Engineering, and AI Agents (autonomous workflows), plus tools like an AI Maturity Index and a centralized results portal. Cadre AI works across industries including professional services, private equity, real estate, financial services, mortgage & lending, construction, retail & e-commerce, and manufacturing & logistics, and focuses on enabling business teams (sales, marketing, customer success, finance, operations, technology, legal, executive leadership) to adopt and scale AI effectively. They position themselves as a practical, conservative partner that prefers activating existing tool capabilities when possible and building custom solutions only when necessary.

📋 Description

• Design and build medallion lakehouses on Databricks, Microsoft Fabric, and Snowflake • Own ingestion from ERPs, CRMs, and SaaS platforms, including change data capture and schema drift handling • Model and transform data with dbt and orchestrate pipelines with Airflow, Dagster, or Lakeflow Jobs • Ship pipelines through CI/CD using GitHub Actions and Declarative Automation Bundles • Build data quality checks and data contracts into pipelines • Configure and govern coding agents in client Databricks repositories • Build production RAG pipelines including parsing, OCR, chunking, embeddings, hybrid retrieval, and reranking • Design GraphRAG systems using knowledge graphs and graph stores • Select and justify retrieval architectures based on use case, cost, and maintenance • Operate vector, full-text, and hybrid search infrastructure with incremental indexing and permission-aware retrieval • Build and deploy retrieval-backed agents on Databricks Agent Bricks • Create governed semantic and metric definitions across dbt, Power BI, Cube, Databricks, and Snowflake • Lead data readiness assessments and document business logic, gaps, and remediation • Expose governed data to agents through MCP • Build golden datasets, evaluation pairs, and leakage-free backtesting splits • Instrument retrieval and agent pipelines and track recall, precision, groundedness, experiments, and model versions • Monitor drift, freshness, and production data gaps • Implement RBAC, row-level security, and masking across data and retrieval systems • Ensure data paths meet SOC 2 and client AI governance requirements • Work with client IT, finance, and operations leaders on scope, access, and build-versus-buy decisions • Record architecture decisions and contribute reusable engineering blocks to Cadre’s internal library

🎯 Requirements

• 5+ years of data engineering experience • At least one production lakehouse designed and operated on Databricks or Microsoft Fabric with medallion architecture • Master’s degree or PhD in Computer Science, Mathematics, Engineering, or related quantitative field • Production RAG pipeline experience, including hybrid retrieval, reranking, chunking, and permission-aware indexing • Experience designing and running GraphRAG or knowledge-graph retrieval • Production data-pipeline orchestration experience with Apache Airflow or Dagster • Expert SQL and strong Python and PySpark • Production experience with dbt or platform-native pipelines and ingestion tools • Daily use and review of coding agents such as Claude Code • Experience authoring semantic or metrics layers • Working ML fluency, including data leakage, time-based validation, class imbalance, precision and recall • Experience building datasets for model or retriever training/evaluation • Experience with Langfuse, Arize Phoenix, Braintrust, or MLflow and MLflow Registry • Hands-on experience building Databricks agents using Agent Bricks or Mosaic AI Agent Framework • Experience running Claude Code or Codex under governed harnesses • Familiarity with Omnigent, Genie Migrate, Agent Bricks CLI, RAG, text-to-SQL, and MCP • Governance experience across Unity Catalog, Purview, or Snowflake RBAC • Client-facing consulting or forward-deployed experience • Professional English fluency • Strong plus: Snowflake Cortex, Palantir Foundry ontologies, RDF/OWL knowledge graphs, DSPy prompt optimization, or LoRA fine-tuning

🏖️ Benefits

• AI-native culture • Access to frontier models and capabilities through partnerships with Anthropic and OpenAI • Growth opportunities and room to move into new teams and initiatives • No bureaucracy; clear accountability and idea-driven culture

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