US – Data Engineer (Pipelines & Structured Markup)

Role Overview

Vulcury is building a manufacturing intelligence infrastructure that converts raw interactions — interviews, transcripts, CAD uploads, commercial discussions — into structured, queriable data objects.

We are seeking a Data Engineer to design and maintain ingestion pipelines and structured transformation workflows that power our internal semantic “truth layer.”

Responsibilities

• Build and maintain ingestion pipelines (Python-based ETL/ELT)

• Design structured transformation workflows using dbt, SQLMesh, or equivalent

• Convert unstructured transcripts and documents into normalized database records

• Maintain PostgreSQL architecture (structured tables, JSONB, indexing strategy)

• Develop attribute extraction frameworks for technical, commercial, and risk signals

• Ensure data quality, consistency, and lineage from raw interaction to structured output

• Collaborate with AI/ML engineers to ensure clean model inputs

Requirements

Required Skills

• Strong Python (data pipelines, orchestration)

• Advanced SQL (PostgreSQL preferred)

• Experience with ETL/ELT frameworks (dbt, Airflow, SQLMesh, etc.)

• Experience handling semi-structured data (JSON, transcripts, document parsing)

• Strong schema design and normalization skills

• Familiarity with cloud storage systems (S3 or equivalent)

Nice to Have

• Experience building semantic layers or knowledge graphs

• Experience working with manufacturing or technical data

• Familiarity with vector databases

Benefits

What Success Looks Like

• Raw interviews automatically convert into structured records

• Attribute confidence scoring flows downstream cleanly

• Data lineage is fully traceable

• Query performance remains stable as data volume scales