Senior Data Engineer

Galaxy Software, Inc.; New York (NY); On-site; USD 170,000 - 200,000; Full time

Benefits offered by this job

Health coverage

Flexible PTO

Paid holidays

Job summary

Galaxy Software, Inc. is an AI-driven investment research company hiring its first dedicated Data Engineer in NYC. You will own ETL/ELT pipelines feeding the AI system, plus models that structure unstructured data into searchable insight.

You’ll shape data contracts and schemas with research and engineering, ensuring accuracy is the product. You’ll build scalable data pipelines, design models across Postgres, S3, and semantic search, and deploy LLMed enrichment with automated quality checks.

Qualifications

• First dedicated Data Engineer role owning data pipelines and models.
• Experience building ETL/ELT pipelines for structured and unstructured data.
• Proven ability to ensure data quality and reliability at scale.
• Familiarity with LLM-powered enrichment and data contracts.

Responsibilities

• Build and run ETL/ELT pipelines for unstructured text, metrics, and third party data.
• Design data models across Postgres, S3, and semantic search.
• Develop LLM-powered enrichment with evaluation for quality.
• Own data quality end-to-end with automated checks and alerts.
• Resolve entities across sources including identifiers and hierarchies.
• Define schemas and data contracts with research, AI, and engineering teams.
• Document lineage, schemas, and runbooks for the platform.
• Work with APIs, databases, and files, handling auth, pagination, and retries.
• Ensure data strategy supports clients plugging in their own data.

Skills

SQL

Python

TypeScript

Data modeling

Data quality

Entity resolution

APIs

ETL/ELT

Tools

Postgres

S3

dbt

Airflow

Snowflake

BigQuery

AWS Bedrock

Job description

Our customer is an AI company in investment research, building an intelligence platform for investors and enterprise strategy teams. Some of the world’s largest funds and companies rely on it to make decisions.

They’re growing fast, and the product only works if the data underneath it is right every time.

Galaxy works with their team on data infrastructure.

The Role

They’re hiring their first dedicated Data Engineer, and you’ll own all of it. That covers the pipelines that feed their AI systems, the models that turn unstructured data into structured, searchable insight, and the systems that will let customers plug their own data into the platform.

You’ll work day to day with their applied AI, research, and engineering teams, but the architecture calls are yours. Their clients make investment decisions on this data, so accuracy isn’t a feature. It’s the product. You’ll set that bar and shape how data works there for years.

You will…

Build and run ETL/ELT pipelines that bring unstructured text, quantitative metrics, and third party datasets into core systems

Design data models across Postgres, S3, and semantic search, picking the right store for each job

Build LLM-powered enrichment pipelines that extract, classify, and structure data, with evals that keep them honest

Own data quality end to end, with automated checks and alerting that catch problems before clients do

Resolve company entities across sources, including identifiers, subsidiaries, hierarchies, and acquisitions

Define schemas and data contracts with research, AI, and engineering as new features ship

Document lineage, schemas, and runbooks as you build

Strong SQL and a feel for how data behaves at scale

Production experience in Python or TypeScript

Their pipelines run on TypeScript today

Experience building reliable integrations with APIs, databases, and files, handling auth, pagination, rate limits, incremental syncs, retries, and schema drift

Comfort with structured, semi-structured, and unstructured data, and the tradeoffs between relational, object, search, and analytical stores

A first principles approach and energy for turning messy data into something solid

Have built LLM-driven pipelines for labeling, moderation, or quality scoring

Have done entity resolution across messy company data

Were early on a data or engineering team and built the function from scratch

Have worked in fintech, financial services, or research and data products

Have used Postgres-native queues, AWS Bedrock, or a warehouse stack like Snowflake, BigQuery, dbt, or Airflow

Details

Location

NYC, in person

Compensation

$170,000-$200,000 base, plus a performance bonus and meaningful equity

• Health coverage
• Flexible PTO
• Paid holidays