Sr. Brokerage Data Engineer

TIAANew York, NY
6d

About The Position

We’re looking for an experienced Brokerage Data Engineer to take full ownership of our custodial data infrastructure, including the key integrations with middle office partners. This is a foundational role in our data platform — ensuring that data from all custodians flows reliably, scalably, and with full transparency into downstream systems. Brokerage data is the authoritative source of truth for client holdings, transactions, and cash. It connects what clients see at their custodian with what we model, trade, and report internally. Any gap, delay, or inconsistency in this data directly impacts trading accuracy, client reporting, and regulatory compliance — making it one of the most critical parts of our platform. We partner with external middle and back office venues – operational hubs that bridge internal portfolio models with external execution and settlement. A tightly integrated custodial data ecosystem ensures that what’s modeled, traded, and reported remains fully synchronized across the investment lifecycle. Our current setup spans multiple pipelines (WS, DTL, and others) across custodians. We’re now seeking a dedicated owner to drive stability, modernization, and scalability in this core area.

Requirements

  • 3+ years of experience in data engineering or backend engineering, ideally within wealth management, asset management, or fintech.
  • Expertise in Python, SQL, and ETL frameworks; experience with orchestration tools.
  • Strong understanding of financial data modeling, API integrations, and schema versioning.
  • Experience working with custodial data, portfolio management, or middle/back-office systems.
  • Proven ownership mindset and ability to operate autonomously in a mission-critical, data-intensive environment.
  • Balance of precision (accuracy, observability) and scale (automation, generalization, performance).

Nice To Haves

  • 5+ years of experience in data engineering or backend engineering, ideally within wealth management, asset management, or fintech.

Responsibilities

  • Own and maintain all custodial data pipelines and back/middle office integration.
  • Build and scale a robust ingestion and reconciliation framework for multi-custodian data (positions, trades, cash, prices, etc.).
  • Identify and resolve data inconsistencies, schema drift, and latency issues across custodial feeds.
  • Collaborate with product, PM, and operations teams to ensure data accuracy for portfolio accounting, trading, and reporting.
  • Define and enforce validation checks, SLAs, and monitoring standards across the data stack.
  • Lead architectural improvements that enhance resilience and reduce technical debt.
  • Partner with adjacent engineering teams (allocations, performance, tax, reconciliation) to ensure system-wide data integrity.
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