Data Engineer — AI-Powered Data Pipelines & Equity

RiseMe; New York (NY); On-site; USD 170,000 - 200,000; Full time

Benefits offered by this job

Health coverage

Flexible PTO

Paid holidays

In-person in New York City

Job summary

Qualitate is seeking a Data Engineer in New York City to own data pipelines and data models that power our AI-native research platform. You’ll build scalable pipelines, curate structured and unstructured data, and enable AI-driven enrichment across the product.

You will design ETL/ELT processes, work with Snowflake/BigQuery, and collaborate with Applied AI and Engineering to shape the data foundation for our customers’ investment workflows.

Qualifications

• Prior experience in data engineering for a technology startup, ideally fintech.
• Strong SQL skills and ability to work with large-scale data.
• Experience building data pipelines and data models.

Responsibilities

• Build and maintain data pipelines. Design ETL/ELT processes ingesting unstructured data, quantitative metrics, and external datasets into core systems.
• Design data models and data systems across relational and non-relational stores.
• Build AI-powered data enrichment pipelines using LLMs and other AI systems.
• Own data quality end-to-end with automated QA checks, monitoring, and alerting.
• Partner cross-functionally with Research, Applied AI, and Engineering to define schemas and reporting needs.
• Document data lineage, schemas, and runbooks as you build.

Skills

SQL

TypeScript

Python

Data pipelines

APIs

Tools

Snowflake

BigQuery

dbt

Airflow

Postgres

S3

AWS Bedrock

Job description

Qualitate is seeking a Data Engineer in New York City to own data pipelines and data models that power our AI-native research platform. You’ll build scalable pipelines, curate structured and unstructured data, and enable AI-driven enrichment across the product.

You will design ETL/ELT processes, work with Snowflake/BigQuery, and collaborate with Applied AI and Engineering to shape the data foundation for our customers’ investment workflows.