Corporate Actions & Data Quality Lead

Polygon.io; United States; On-site; USD 120,000 - 150,000; Full time

Job summary

A leading financial technology company is seeking a Corporate Actions & Data Quality Lead to ensure the accuracy and reliability of corporate actions and reference datasets. This senior role involves owning the full lifecycle of corporate actions, developing backtesting frameworks, and implementing data quality standards. Ideal candidates will have deep expertise in global corporate actions and strong skills in data anomaly detection, alongside a commitment to data integrity and collaboration with cross-functional teams.

Qualifications

• Deep expertise in global corporate actions, including lifecycle events and adjustment logic.
• Experience working with reference data from major vendors like Bloomberg or Refinitiv.
• Comfort with structured data and understanding data sequences over time.

Responsibilities

• Own the full lifecycle of corporate actions ensuring accuracy and completeness.
• Develop backtesting frameworks to validate corporate action logic.
• Build automated anomaly detection and quality monitoring rules.

Skills

Expertise in global corporate actions

Data anomaly detection

Data quality engineering

SQL or similar structured data

Strong communication skills

Job description

Overview

About The Role We are looking for a Corporate Actions & Data Quality Lead who will own the correctness, consistency, and long-term reliability of our corporate actions and reference datasets. This role blends domain expertise in global corporate actions with data quality engineering, anomaly detection, and systematic backtesting.

You will design and maintain the validation logic, monitoring frameworks, and historical backtests that ensure our corporate actions adjustments, lifecycle transitions, and reference data remain accurate and stable across time. This is a senior, high-ownership role that sits at the heart of data integrity for our platform.

Responsibilities

• Own the full lifecycle of corporate actions—splits, dividends, mergers, symbol changes, spin-offs—ensuring accuracy, completeness, and correct historical adjustments.
• Develop and run backtesting frameworks that validate corporate action logic across historical datasets, comparing expected vs. actual outcomes and surfacing discrepancies.
• Build automated anomaly detection, reconciliation checks, and quality monitoring rules across multiple data sources (exchanges, issuers, regulatory filings, vendor feeds).
• Identify, triage, and resolve inconsistencies in reference data, instrument metadata, and lifecycle transitions.
• Partner with engineering to strengthen ingestion logic, normalization rules, and lifecycle pipelines affected by corporate actions and reference changes.
• Document corporate action logic, adjustment methodologies, and lifecycle decisions so downstream teams can rely on clear, explainable rules.
• Collaborate with product, data, and derived dataset teams to ensure adjustments and lifecycle events propagate correctly across every surface.
• Work with global exchanges and data partners to clarify ambiguous events and resolve conflicting information.
• Establish and maintain systematic data quality standards that prevent issues from re-occurring.

Skills & Qualifications

• Deep expertise in global corporate actions, including lifecycle events, adjustment logic, announcement types, and exchange-specific nuances.
• Experience working with reference data and corporate action feeds from exchanges, issuers, or major vendors (Bloomberg, Refinitiv, ICE, etc.).
• Strong ability to detect and diagnose data anomalies, inconsistencies, missing events, or incorrect adjustments.
• Experience designing or operating validation pipelines, reconciliation systems, or backtest-like frameworks for data correctness.
• Comfort working with structured data (SQL or similar) and understanding event sequences over time.
• Clear, precise communication—able to explain complex lifecycle logic to product, engineering, and customers.
• A high-ownership mindset, with a drive to close the loop on root causes and improve systems long-term.
• Familiarity with exchange circulars, regulatory filings, and issuer notices is a plus.
• Understanding of how corporate actions influence historical OHLC, factors, and analytical datasets is a plus.
• Experience with anomaly detection tools, statistical checks, or data quality SLOs is a plus.
• Knowledge of multi-asset reference data structures is a plus.

About Massive

At Massive we are on a mission to help developers build the future of fintech. We are committed to democratizing access to the world's financial market data and enabling developers to build the future of fintech. Join us and be part of a team that is revolutionizing the way we interact with money and value.

If you are a passionate problem-solver who thrives in a dynamic and innovative environment, we encourage you to apply!