Staff Engineer, Data Platform

NationGraph; Toronto; Hybrid; CAD 140,000 - 210,000; Full time

Job summary

NationGraph is seeking a Staff Engineer, Data Platform to own the end-to-end external data platform, transforming fragmented government information into a proprietary data advantage. You’ll design systems for discovery, acquisition, extraction, normalization, entity resolution, validation, storage, serving, and monitoring across thousands of sources.

You’ll collaborate with Product, ML Research, and Infrastructure to shape architecture, leverage Python, Go, PostgreSQL, Redis, Docker, and

Qualifications

• Strong experience with Python/Go for building data platforms.
• Proficient in SQL and large-scale data processing.
• Solid understanding of distributed data systems and data pipelines.

Responsibilities

• Own our external data platform end-to-end across discovery, acquisition, extraction, normalization, entity resolution, validation, storage, serving, and monitoring.
• Design architecture for systems spanning discovery, acquisition, extraction, normalization, and data quality checks.
• Map the world of government data and understand how it is published and evolves.
• Build for messy, real-world data and changing schemas across thousands of sources.
• Experiment with AI/LLMs to rethink the data stack and improve data flywheels.

Skills

Python

Go

SQL

Distributed systems

Tools

PostgreSQL

Redis

Docker

Kubernetes

Job description

Staff Engineer, Data Platform

About NationGraphNationGraph is building the data and intelligence layer for the public sector.More than 110,000 state and local government agencies across the U.S. independently publish information about:How they operateWhat they buyWho they work withWhat problems they are trying to solveThat information is fragmented across millions of websites, documents, databases, procurement systems, meeting records, and public records.NationGraph turns that information into structured, connected, actionable intelligence for businesses selling to government.Founded in 2024, NationGraph is dedicated to making uncommon knowledge common, because public data should actually be public.

The Role

We’re looking for a Staff Engineer, Data Platform to own one of the most important technical problems at NationGraph: turning the outside world’s fragmented government information into a proprietary data advantage.This is not a traditional data engineering role focused on maintaining a warehouse or internal analytics.You’ll own the technical ecosystem that:

• Discovers external data
• Acquires it reliably
• Understands and extracts information from it
• Normalizes and connects it
• Validates its quality
• Makes it available to NationGraph’s products and models

The scope starts with more than 110,000 independent state and local government agencies, but extends to federal data, Canada, and eventually public-sector information globally.You’ll work across:

• Data engineering
• Distributed systems
• Information retrieval
• Data modeling
• LLMs and agents
• Applied ML
• Entity resolution
• Knowledge graphs

You’ll partner closely with Product, ML Research, and Infrastructure to determine both:How we acquire dataWhat data NationGraph should have that nobody else doesWhat

What You’ll DoOwn our external data platform end-to-endDesign systems spanning discovery, acquisition, extraction, normalization, entity resolution, validation, storage, serving, and monitoring.Establish the architecture and abstractions other engineers build on.Map the world of government dataDevelop a deep understanding of where government information lives.Understand how it is published, how it changes, and how information across thousands of institutions can be connected.Build systems for messy, real-world dataWork across government websites, APIs, procurement systems, PDFs, spreadsheets, meeting records, and public records.Build for changing schemas, broken sources, conflicting records, and edge cases.Use AI to rethink the traditional data stackWork with our ML Research team to use LLMs, agents, and emerging models to:Discover new sourcesUnderstand unfamiliar schemasExtract structured informationResolve entitiesMonitor data qualityDetect when sources changeBuild proprietary data flywheelsCreate systems where more data improves our models.Use better models to discover and understand more data.Continuously expand NationGraph’s underlying knowledge graph.Set technical directionDefine the architecture for how NationGraph acquires and represents public-sector information.Make decisions that will shape the platform over the next several years.Help determine which technical investments create the strongest long-term data advantage.

You Might Be a Good Fit If

You’re an unusually strong engineer who genuinely enjoys working with data.You’ve owned significant production data systems end-to-end.You enjoy the detective work of making sense of unfamiliar, messy datasets.You’re strong in Python, Go, or another systems/backend language.You’re highly proficient with SQL.You understand distributed data systems, including:OrchestrationIdempotencyBackfillsRetriesObservabilityLineageFailure recoveryYou have experience with one or more of:

• Large-scale external data
• Crawling
• Information retrieval
• Entity resolution
• Knowledge graphs
• Document processing

You’re excited about using LLMs and modern ML as components of data infrastructure.You care deeply about data quality, correctness, and reliability.You have strong product judgment and can reason about what data is actually worth acquiring, not just how to acquire it.You thrive in ambiguity and would rather create the architecture than be handed one.We’re particularly interested in backgrounds spanning:

• Alternative data
• Quantitative research infrastructure
• Search and crawling
• AI data infrastructure
• Knowledge graphs
• Large-scale document processing
• Data aggregation

None of these are requirements.

Our Engineering Stack

• Backend: Python, Go, PostgreSQL
• Infrastructure: Redis, Docker, Kubernetes
• Frontend: React, TypeScript
• AI / ML: LLMs, agents, proprietary models, and emerging frontier-model research

Our stack will evolve. At Staff level, you’ll help decide how.

Why NationGraph

Own a foundational problemA large part of this architecture still needs to be invented.You’ll have significant ownership over how NationGraph discovers, acquires, represents and serves public-sector information.Work on a genuinely hard data problemThere is no single API for American government.There are tens of thousands of institutions, millions of sources, inconsistent schemas, and enormous amounts of information buried in systems never designed for machines.Build a real data moatWe believe a major long-term advantage in applied AI will come from proprietary context and data.Government contains enormous amounts of valuable information that is technically public but practically inaccessible.Your job is to change that.Work with exceptional peopleYou’ll work closely with the CEO, CTO, and a small engineering and research team.The team has backgrounds spanning high-scale infrastructure, quantitative finance, AI, and startups.Have real ownershipWe move quickly.We operate with very little bureaucracy.Engineers have significant ownership over technical decisions and product outcomes.If the idea of building the data infrastructure to map and understand how government works sounds exciting, we’d love to talk.