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Senior Data Engineer

USAFull-time$62,000–$102,0002026-10-05 → 2026-10-08

Core

Designing data foundations, retrieval patterns, and scalable data services for agentic and machine learning solutions.

Builds

Production-grade data platforms, retrieval-system pipelines, and data infrastructure for AI/LLM lifecycle

Domain

Data engineering + AI/ML engineering

Deliverable

production ML models

Required skills

End-to-end data pipelines, Cloud data platforms (AWS/Azure/GCP), Databricks, Python, Column-oriented databases (BigQuery/Redshift), NoSQL databases (DynamoDB/Bigtable/Cosmos DB), SQL databases (SQL Server/Oracle/MySQL), Streaming and batch integrations (Glue/Dataflow/Data Factory/Spark), Data modeling and warehouse design, CI/CD and production support, MLOps, AI engineering patterns (context engineering, RAG, agent architectures), Retrieval-system pipelines (parsing, chunking, embeddings, vector/graph DBs), Agent platforms and orchestration, AI evaluation data infrastructure, Agent state modeling, Snowflake (zero-copy), AI/ML lifecycle support (deployment, monitoring, validation)

Preferred skills

Developer certification in cloud/data platforms, Experience in retail/financial services/energy/CPG/logistics/manufacturing, Agile/product methodologies in consulting

Technologies

AWS Lambda, Redshift, Azure, BigQuery, Cloud, Cosmos DB, Databricks, ETL, LLM, Machine Learning, MLOps, MySQL, NoSQL, Oracle, Python, SQL, Snowflake, Spark

Responsibilities

Design data foundations and retrieval patterns for AI/ML solutions, Build scalable data services for agentic workflows, Apply data lineage and provenance rigor to context sources, Support AI/ML and LLM lifecycle needs including model deployment and evaluation

Seniority

Senior, hands-on IC