Data Operations Analyst

Finstock, Inc.; United States; Remote; USD 70,000 - 110,000; Full time

Job summary

Finstock, Inc. is seeking a detail-oriented Data Operations Analyst to support its AI-powered financial research, trading analytics, and market intelligence platforms. The role focuses on maintaining accurate, reliable datasets used for analytics and AI-assisted research.

The successful candidate will monitor data workflows, validate and reconcile financial information, and collaborate with Data Engineering, AI, Product, and Research teams in a fully remote environment.

Qualifications

• 2+ years in data operations, data analysis, BI, financial data, or related field.
• Strong SQL and advanced spreadsheet knowledge.
• Experience validating, reconciling, and troubleshooting structured datasets.
• Excellent written communication and documentation skills.
• Ability to work independently and remotely.

Responsibilities

• Monitor financial data feeds, pipelines, and dashboards to ensure reliable data delivery.
• Validate and reconcile market prices, fundamentals, and metadata.
• Identify missing, duplicated, or inconsistent data and coordinate fixes.
• Write SQL queries and use spreadsheets or scripts to resolve data-quality issues.
• Maintain data dictionaries, validation rules, and operational docs.
• Support onboarding and testing of new data sources and vendors.
• Communicate data limitations clearly to stakeholders.
• Track data-quality metrics and incident resolution times.
• Ensure data handling complies with security and privacy requirements.

Skills

SQL

Spreadsheets

Data validation

Documentation

Attention to detail

Remote collaboration

Education

Bachelor’s Degree in Data Analytics/Computer Science/Finance/Business

Tools

Python

APIs

BI tools

dbt

Data warehouses

Job description

Finstock, Inc. is seeking a detail-oriented Data Operations Analyst to support its AI-powered financial research, trading analytics, and market intelligence platforms. The role focuses on maintaining accurate, reliable, and high-quality financial and market datasets used for analytics and AI-assisted research.

The successful candidate will monitor data workflows, validate and reconcile financial information, investigate data discrepancies, and collaborate with Data Engineering, AI, Product, and Research teams. This position is ideal for professionals who have strong SQL skills, analytical thinking, and experience managing structured datasets in a remote environment.

Key Responsibilities

• Monitor financial data feeds, pipelines, scheduled jobs, and operational dashboards to ensure reliable data delivery.
• Validate and reconcile market prices, company fundamentals, filings, corporate actions, macroeconomic indicators, news, and research metadata.
• Identify missing, duplicated, outdated, or inconsistent data and coordinate solutions with relevant teams.
• Write SQL queries and use spreadsheets or scripts to investigate and resolve data-quality issues.
• Maintain validation rules, exception reports, data dictionaries, and operational documentation.
• Support onboarding and testing of new data sources, APIs, and third-party data vendors.
• Respond to internal data requests and communicate data limitations clearly.
• Track data-quality metrics, recurring issues, resolution times, and operational performance.
• Ensure data handling follows security, privacy, licensing, and confidentiality requirements.

Requirements

• 2+ years of experience in data operations, data analysis, business intelligence, financial data, or a related field.
• Strong SQL skills and advanced spreadsheet knowledge.
• Experience validating, reconciling, and troubleshooting structured datasets.
• Strong attention to detail with the ability to identify data inconsistencies.
• Excellent written communication and documentation skills.
• Ability to work independently and collaborate effectively in a remote environment.
• Must be authorized to work in the United States.

Strong knowledge of:

• SQL queries, spreadsheets, scripting, and data-quality analysis.
• Financial datasets, market data validation, and reconciliation processes.
• Data documentation, operational procedures, and quality-control frameworks.

Preferred Qualifications

• Experience in fintech, capital markets, investment research, market data, or financial services.
• Familiarity with equities, ETFs, indices, FX, commodities, financial statements, filings, and corporate actions.
• Working knowledge of Python, APIs, BI tools, dbt, or data warehouses.
• Experience with data-quality monitoring, incident management, data governance, or vendor data feeds. Bachelor’s Degree in Data Analytics, Computer Science, Finance, Business, or a related field