Member of Technical Staff, Data Pipelines

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 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 Core Competencies 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 Programming SQL Proficiency Data Engineering Distributed Processing Financial Data Experience Hard Skills Data Pipeline Design Data Infrastructure Data Transformation Data Governance Point-in-Time Querying Reproducibility Schema Management Data Normalization Event Time Processing Machine-Consumable Data Systems Soft Skills Strong Judgment Rigor About Correctness Industry Keywords AI Research Market Data Security Identifiers Corporate Actions Quantitative Research #J-18808-Ljbffr Jobtailor