Manager of Data Engineering

Key Responsibilities

• Technical Execution: Lead technical delivery by translating product roadmaps into development cycles; own task breakdown and workflow management.
• Strategic Data Architecture: Architect and implement multi-modal data pipelines processing structured parts catalogs and unstructured sources (PDFs, Word, diagrams) into Vector and Graph data stores.
• Knowledge Layer Development: Design and optimize storage of embeddings in Vector Databases (e.g., Pinecone, ChromaDB, Vertex AI Search) and Graph Databases (e.g., FalkorDB, Neo4j) for multi-step agentic reasoning.
• Agent-Driven Development: Integrate autonomous coding agents into daily workflow for planning, generating, and refactoring data infrastructure and microservices.
• Evaluation Pipelines: Collaborate with AI Engineers to build "Gold Dataset" pipelines for automated verification and quality measurement of AI outputs.
• Microservices: Develop and maintain scalable data services and RESTful APIs using Python (FastAPI/Django).
• Cloud Operations: Deploy and monitor high-scale data workloads on GCP (Vertex AI, BigQuery); ensure reliability, security, and cost-effectiveness.

Skills and Experience

• 10+ years of Software/Data Engineering experience with proven history of leading technical teams.
• Track record of designing and building production-grade AI data systems.
• Technical Stack: Advanced Python (FastAPI, Pydantic, SQLAlchemy) and SQL mastery for scalable microservices.
• AI: Hands-on experience with Vector Databases (Pinecone, ChromaDB), RAG pipelines, and GraphRAG patterns.
• Data Tooling: Deep experience with Prefect (preferred), Apache Airflow/Cloud Composer, BigQuery, DataProc.
• Cloud Infrastructure: Experience with GCP, AWS for deploying data workloads at scale.
• Coding Agent: Demonstrated proficiency using coding agents to accelerate SDLC and plan/complex engineering tasks.

Job Details

Location: Remote, Dallas, TX
Job Type: remote
Posted: 23 days ago
Categories: Software Engineering