Member of Technical Staff, Data Pipelines

Healthcare powered by ATG intelligence

Data pipelines engineer building AI research and production infrastructure for ATG, an AI lab and autonomous wealth manager. Owning financial data ingestion, modeling, reliability, and governance.

Posted 8/5/2026full-timeNew York City • New York • 🇺🇸 United StatesLead💰 $150,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining robust data pipelines and infrastructure for large-scale AI research, with a strong focus on data correctness, governance, and the ability to handle complex, unstructured datasets. Proficient in Python and SQL, with experience in building reliable data systems that support AI-native applications.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyData EngineeringDistributed ProcessingFinancial Data Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignData InfrastructureData TransformationData GovernancePoint-in-Time QueryingReproducibilitySchema ManagementData NormalizationEvent Time ProcessingMachine-Consumable Data Systems

Soft Skills

Strong JudgmentRigor About Correctness

Industry Keywords

AI ResearchMarket DataSecurity IdentifiersCorporate ActionsQuantitative Research

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design, build, and maintain robust data pipelines and infrastructure for large-scale AI research, applied AI, and production systems
Own the data platform end to end, including ingestion, storage, transformation, cataloging, governance, and access
Build reliable pipelines for large, heterogeneous datasets, schema changes, late data, revisions, backfills, and vendor failures
Ensure research-grade correctness through point-in-time data, lineage, versioning, reproducibility, and prevention of look-ahead and survivorship bias
Create trusted data products by normalizing identifiers, timestamps, corporate actions, reference data, and unstructured sources into accessible datasets and APIs
Enable AI-native systems with permission-aware interfaces, metadata, datasets, and benchmarks for researchers and agents
Partner with research and engineering to turn ambiguous problems into durable data capabilities

Requirements

What you’ll need

Exceptional software and data engineering skills
Strong Python and SQL skills
Experience with distributed processing and modern data infrastructure
Demonstrated ability to design, deploy, operate, and improve business-critical data systems at scale
Expertise in revisions, event time versus knowledge time, reproducibility, and point-in-time querying
Strong judgment with messy, changing, unstructured, or adversarial data
Rigor about correctness, provenance, and privacy
Daily use of coding agents and ability to build safe, well-described, machine-consumable data systems
Financial-data experience strongly preferred, including market data, security identifiers, corporate actions, or quantitative research

Benefits

Comp & perks

Equity offered
Work on AI with a massive market opportunity
Early team of repeat founders backed by top investors
High agency, talent dense, zero bureaucracy