Data Engineer

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RemoteFull-timeData EngineeringUnited States preferredFinancial data infrastructureCloud / ETL / ELT

Finstock Careers

Data Engineer

Build scalable data pipelines, data quality systems, financial datasets, and secure data infrastructure for Finstock's AI-powered financial research and market intelligence platform.

Remote - United States preferred Full-time USD $105,000-$140,000/year

Role metadata

Company

Finstock, Inc.

Location

Remote - United States preferred

Type

Full-time

Compensation

USD $105,000-$140,000 annual base salary

Reporting line

Engineering Lead

Tools

Microsoft Teams, Outlook, Microsoft 365, GitHub, cloud data platforms

About Finstock, Inc.

Finstock, Inc. builds AI-powered financial research, trading analytics, quantitative research, and market intelligence tools for experienced market users, analysts, research teams, and institutions.

Our products rely on clean, reliable, secure, and scalable data infrastructure across market data, financial statements, company disclosures, research workflows, analytics tools, and user-facing product features.

About The Role

We are hiring a Data Engineer to help build and maintain the data infrastructure behind Finstock's financial research and market intelligence platform.

In this role, you will design, develop, test, and operate data pipelines that ingest, clean, transform, validate, and deliver financial and market-related data to internal systems, analyst workflows, AI-assisted research tools, and user-facing product features.

This is a remote role with a preference for candidates based in the United States. Candidates in other countries may be considered where Finstock, Inc. is able to engage them in compliance with applicable employment, tax, data protection, and operational requirements.

Key Responsibilities

• Design, build, and maintain scalable data pipelines for financial market data, company fundamentals, filings, corporate actions, news, research metadata, analytics outputs, and product usage data.
• Develop robust ETL/ELT workflows for batch and near-real-time data processing.
• Build and maintain data models, data marts, warehouse tables, and analytical datasets used by product, research, AI, and engineering teams.
• Implement data quality checks, validation rules, reconciliation workflows, anomaly detection, and automated monitoring.
• Improve data reliability, latency, lineage, observability, and documentation across Finstock's data infrastructure.
• Integrate data from APIs, vendor feeds, public sources, internal systems, and approved third-party data providers.
• Collaborate with analysts, product managers, AI engineers, backend engineers, and leadership to translate business and research requirements into reliable data products.
• Support financial research workflows involving equities, ETFs, indices, FX, crypto assets, commodities, macro indicators, and cross-asset market intelligence.
• Build secure data access patterns, permission controls, and audit-friendly workflows for sensitive or user-scoped data.
• Maintain documentation for data sources, schemas, transformation logic, pipeline ownership, data quality assumptions, and known limitations.
• Troubleshoot pipeline failures, data discrepancies, performance bottlenecks, and production incidents.
• Contribute to cloud infrastructure, CI/CD workflows, testing standards, and engineering best practices for data systems.
• Ensure data usage follows applicable licensing, confidentiality, security, privacy, and compliance requirements.
  
  

Required Qualifications

• 3+ years of professional experience in data engineering, backend data systems, analytics engineering, or a related technical role.
• Strong proficiency in SQL and Python.
• Experience building and maintaining production-grade ETL/ELT pipelines.

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• Experience with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure.
• Experience with data warehouses or lakehouse technologies such as Snowflake, BigQuery, Redshift, Databricks, Delta Lake, or similar systems.
• Familiarity with orchestration and transformation tools such as Airflow, Dagster, Prefect, dbt, or similar workflow tools.
• Strong understanding of data modeling, schema design, partitioning, indexing, data quality testing, and pipeline observability.
• Ability to work with APIs, structured data, semi-structured data, JSON, CSV, Parquet, relational databases, and time-series datasets.
• Strong debugging, documentation, and communication skills.
• Ability to work independently in a remote environment and collaborate effectively across product, engineering, and analyst teams.
• Professional commitment to data security, confidentiality, and responsible handling of financial and user-related data.
• Ability to work remotely in compliance with applicable laws and eligibility requirements.
  
  

Preferred Qualifications

• Experience working with financial market data, trading analytics, investment research platforms, fintech products, or capital markets infrastructure.
• Familiarity with equities, ETFs, indices, FX, crypto assets, commodities, financial statements, corporate actions, and market data vendors.
• Experience with streaming or event-driven systems such as Kafka, Kinesis, Pub/Sub, or similar technologies.
• Experience with data APIs, vector databases, search infrastructure, knowledge graphs, or retrieval systems used in AI-assisted products.
• Experience with PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch/OpenSearch, or time-series databases.
• Experience with Docker, Kubernetes, Terraform, GitHub Actions, CI/CD, infrastructure-as-code, and production monitoring tools.
• Experience supporting AI, machine learning, LLM, or analytics products with reliable data pipelines.
• Familiarity with data governance, access control, audit trails, privacy controls, and vendor data licensing requirements.
• Interest in financial research, market intelligence, quantitative analytics, and AI-assisted research workflows.
  
  

What You Will Work On

You May Work On Projects Such As

• Building market data ingestion pipelines for cross-asset research workflows.
• Creating clean and reliable datasets for financial analytics, charts, dashboards, and AI-assisted research features.
• Designing data quality checks for prices, fundamentals, filings, corporate actions, and macroeconomic data.
• Improving data freshness, pipeline monitoring, lineage, and alerting.
• Supporting internal analyst workflows with curated financial datasets and automated reporting layers.
• Building secure user-scoped data workflows for local workspace features and product personalization.
• Helping engineering and product teams scale data infrastructure as the platform grows.
  
  

What You Will Gain

• Opportunity to build data infrastructure for an AI-powered financial research and market intelligence platform.
• Direct collaboration with product, engineering, AI, and regional analyst teams.
• Exposure to financial market data, quantitative analytics, research workflows, and AI-assisted product development.
• Remote work with a distributed international team.
• A company email account and access to approved work tools, including Microsoft 365, Outlook, Teams, GitHub, and company-approved productivity tools, subject to internal security and usage policies.
• Opportunity to participate in company offsite activities, including possible Hong Kong offsites, subject to business schedule, travel eligibility, visa/documentation requirements, and company approval. Approved business-related travel, accommodation, and reasonable expenses will be covered by the company.
  
  

Important Role Boundaries

This is a data engineering role supporting financial research infrastructure and product data systems.

The role does not require or permit the employee to:

• Provide personalized investment, legal, tax, accounting, or financial advice to users or clients.
• Recommend that any individual buy, sell, or hold a security based on personal circumstances.

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• Execute trades or manage client funds.
• Handle client assets, deposits, or payments.
• Promise or imply investment returns, trading profits, or risk-free outcomes.
• Use unauthorized data sources, violate third-party data terms, or bypass licensing restrictions.
• Request applicants to pay any application fee, training fee, software fee, equipment fee, or onboarding fee.
  
  

Equal Opportunity Statement

Finstock, Inc. considers qualified applicants based on role-related skills, experience, technical ability, work quality, availability, and applicable engagement requirements. We do not make hiring decisions based on age, gender, gender identity, religion, ethnicity, race, national origin, disability, sexual orientation, marital status, family status, veteran status, or any other status protected by applicable law.

Role Application

Apply for this role

Submit your information for the Data Engineer role.

Open

Full name *

Email address *

Country / region *

Current city / time zone *

Phone number *

LinkedIn profile URL *

Resume/CV link *

Work authorization / remote work eligibility *

Years of professional data engineering experience *Select experience rangeLess than 3 years3-5 years5-8 years8+ years

Current or most recent role *

Expected annual compensation *

Availability / earliest start date *

Financial data / fintech experience *Select experience levelNo direct financial data experience yetSome exposure to financial or market dataProfessional fintech / trading / market data experienceExtensive capital markets data infrastructure experience

GitHub profile URL or technical portfolio link *

Writing sample or technical documentation link

Cloud platform experience *

Data engineering skills *

Infrastructure / DevOps skills *

Relevant certifications

Describe one production data pipeline or data platform you built or maintained. Include the data sources, transformation logic, quality checks, and operational challenges. *

Describe your experience with data quality, observability, reconciliation, lineage, or incident response. *

Describe your interest in financial market data, AI-assisted research tools, or market intelligence infrastructure. *

Additional notes

I confirm that the information I provide is accurate and that I understand this role does not involve giving personalized investment advice, executing trades, or managing client funds.

Role summary

Open

Company Finstock, Inc.

Location Remote - United States preferred

Workplace type Remote

Job type Full-time

Compensation USD $105,000-$140,000 annual base salary

Reporting line Engineering Lead

Tools Microsoft Teams, Outlook, Microsoft 365, GitHub, cloud data platforms, and company-approved productivity tools

Status Open

Apply now