Data Engineering Consultant

SUMMARY

Build the data foundation that grounds AI agents on facts they can trust. You turn raw, messy, multi-source data — structured feeds and unstructured content alike — into canonical, provenance-tagged, SLA-fresh Gold data that the Knowledge & Intelligence layer serves. Working with business leaders and internal customers, you set the design standards and assurance processes that keep the pipeline compatible, operable, and traceable end to end. This is hands-on data engineering where correctness and lineage aren't nice-to-haves — they're the product. You develop fundamentally new approaches to pull meaning out of data, and every record you land answers the question “where did this come from, and can we trust it?”

What You'll Own

• • The medallion pipeline. Take landed data through Bronze → Silver → Gold — conforming structured sources and extracted content to Gold within its freshness SLA, with traceable lineage at every hop. • • Entity resolution. Own the resolve gate that turns many sources into one canonical identity — the join everything downstream depends on. • • Model-based extraction lanes. Build the NLP- and LLM-assisted lanes that pull structure out of unstructured content across many content types — HTML, PDF, DAM assets, and more — tagged as evidence, not fact. • Provenance and trust. Tag provenance and trust tier on every record. Quarantine what fails the gate with its reason attached, rather than silently dropping it. • • Performance at scale. Keep…