Market Data Operations Analyst (1DA3692)

Referment; United States; On-site; USD 85,000 - 125,000; Full time

Job summary

Referment is seeking a Market Data Operations Analyst to support SaaS clients by monitoring market data generation processes and ensuring data integrity and SLA adherence.

The role blends technical and functional support with incident management and coordination across clients, vendors and internal teams to keep data operations running smoothly.

Qualifications

• Bachelor's degree or equivalent professional experience.
• Strong Python for ad-hoc data analysis and automation.
• Proficiency in Excel; SQL knowledge beneficial.
• Understanding of derivatives markets and risk concepts.

Responsibilities

• Define, implement and run standard operating procedures for clients' market data operations.
• Perform daily monitoring and verification of market data deliveries across multiple clients.
• Improve processes by optimizing and automating manual checks.
• Respond to daily operational requests and market data queries from clients and internal groups.
• Monitor, triage and resolve data-quality issues on data feeds; escalate as needed.
• Engage with vendors on market data availability and quality.
• Coordinate releases and deployments with clients and internal teams.
• Act as incident manager for market data incidents and post-mortems.
• Assist financial-institution clients with the market data API platform.

Skills

Python

Excel

SQL

Education

Bachelor's degree

Job description

Referment is working with a capital markets fintech whose analytics software is used by financial institutions to price derivatives and manage risk. This Market Data Operations Analyst supports the firm's SaaS clients by monitoring the market data generation processes behind its data management framework, protecting the integrity and quality of the data clients depend on. The role blends technical and functional support with incident management and coordination - working with clients, vendors and internal product, engineering and professional services teams to keep data operations running to SLA.

The Role

• Define, implement and run standard operating procedures for clients' market data operations.
• Perform daily monitoring and verification of market data deliveries - including scheduled intraday and end-of-day snapshots across multiple clients - checking batches and feeds for operational integrity and SLA compliance.
• Improve processes by optimising and automating manual checks.
• Respond to daily operational requests and market data queries from clients and internal groups.
• Monitor, triage and resolve technical and data-quality issues on data feeds, escalating to developers, vendors or other stakeholders as needed.
• Engage with vendors on market data availability, delivery and quality.
• Coordinate releases and production patch deployments with clients and support development teams on parallel runs.
• Act as incident manager for market data incidents, leading post-mortems and root cause analysis.
• Assist financial-institution clients with the market data API platform.

What We're Looking For

• A bachelor's degree from a leading engineering university or equivalent professional experience.
• Good Python skills for ad-hoc data analysis and automating manual processes.
• Proficiency in Microsoft Excel; practical exposure to SQL is beneficial.
• Understanding of exchange-traded and OTC derivatives (forwards, futures, options) across asset classes including rates, commodities, credit, equities and FX, with familiarity with concepts such as volatility and beta.
• Strong troubleshooting abilities and good English communication skills.
• Willingness to work a US shift (3:00 PM to 11:30 PM MST) when required.

Desirable

• Working knowledge of cloud services, ideally AWS (Step Functions, Lambda, EC2, DynamoDB).
• Using Excel, Python and SQL together for investigation and ad-hoc analysis of market data issues.

This could suit...

market data or operations analysts with a derivatives background who combine scripting skills with hands-on production support.

#Referment