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Data Engineer

Job Description: Remote | Full-Time

About the Role Relish is building a knowledge graph to unify the structured and unstructured customer data that flows through our Data Assure and Invoice AI products. This data — spanning ERP transactions, invoices, purchase orders, vendor records, contracts, and procurement documents — will power a new generation of alerts, fraud/risk detection, and customer insights. We're looking for a Data Engineer to own the pipelines that make this possible.

Key Responsibilities

Build and maintain ETL/ELT pipelines that ingest structured data from ERP systems (SAP, Oracle, and similar enterprise platforms) and unstructured data (invoices, contracts, PDFs, and procurement documents) into a graph-ready format
Develop entity resolution and relationship mapping logic to populate and maintain the Relish knowledge graph
Partner with our NLP/ML engineer on extraction pipelines that transform raw document content into structured graph entities and relationships
Integrate with our existing Azure-based infrastructure, including Azure Functions and Microsoft Graph API touchpoints
Maintain pipeline orchestration, scheduling, and monitoring — ensuring data is fresh, clean, and trustworthy
Support the query and alerting layer that surfaces fraud signals, risk patterns, and customer insights from the graph
Contribute to ontology and schema decisions alongside the Knowledge Graph Engineer and domain experts in invoice/procurement data
Ensure data quality, lineage, and governance standards across all pipeline stages

Our Stack

Layer

Technologies

Language

Python (primary), TypeScript/JavaScript

Cloud

Azure (Azure Functions, event-driven services)

Data pipelines

Airflow / Dagster (orchestration), custom ETL

Graph DB

Neo4j or Amazon Neptune (in evaluation)

Unstructured processing

LLM-based extraction, NER pipelines, PDF/document parsing

Enterprise integrations

SAP, Oracle, ERP connectors

APIs

Microsoft Graph API, HubSpot API, REST

AI/ML layer

Anthropic API (Claude), agentic workflows

Containers

Docker, containerized deployments

What We're Looking For

Must-have

3–6 years of data engineering experience with a strong Python foundation
Proven experience building pipelines for both structured (relational, ERP) and unstructured (documents, PDFs, emails) data
Familiarity with graph databases (Neo4j, Neptune, or similar) and graph query languages (Cypher or Gremlin)
Experience with cloud-native data infrastructure, ideally on Azure
Solid understanding of entity resolution, deduplication, and data quality practices
Ability to work in a fast-moving, resource-conscious R&D environment

Strong plus

Prior exposure to invoice, procurement, or ERP data domains
Experience with NLP pipelines (NER, relation extraction, LLM-based structured output)
Familiarity with LLM APIs (Anthropic, OpenAI) for data extraction workflows
Knowledge of ontology design or semantic data modeling (RDF, OWL)

Key Certifications Worth Having

Credential

Why It Matters at Relish

Neo4j Certified Professional

Direct alignment with our graph DB path

Microsoft Azure Data Engineer Associate (DP-203)

Matches our Azure infrastructure

Databricks Certified Associate

Useful if pipeline scale grows

dbt Analytics Engineering Cert

Strong signal on data transformation practices

CS/Data Engineering MS

Valued but not required

Why Relish You'd be joining a ~$15M ARR enterprise SaaS company at a meaningful inflection point — the knowledge graph initiative is core R&D that will directly shape the next generation of Data Assure and Invoice AI. You'll have real ownership, work across the full data stack, and see your work surface directly in customer-facing fraud and risk products.

Pay: $160,000.00 - $180,000.00 per year

Benefits: