Standard Metrics logo
Standard Metrics
Posted 69 days agoVerified live 2d ago

Data Solutions Engineer

Brief overview

Remote
3+ yrsMinimum
SQLPythonREST APIsPrompt EngineeringLarge Language Models (LLM)SnowflakedbtData Integration ToolsFund AccountingInvestment Data WorkflowsMCP ServersAI Agents

About the company

Standard Metrics logo
Standard Metricsstandardmetrics.io

Standard Metrics is a financial platform for startups and investors.

Job description

Summary

Standard Metrics is an AI-driven financial data platform that helps investors and their portfolio companies make more informed, forward-looking decisions with automated reporting and benchmarking tools. The Data Solutions Engineer will serve as the technical owner for customer-facing data workflows and integrations, collaborating with customers to solve data challenges and build impactful solutions.

Responsibilities

  • Partner directly with customers to identify data challenges and design technical solutions - connecting data sources, configuring integrations, automating recurring workflows, and deploying custom reports
  • Deploy and optimize AI-powered tools and workflows for customers; educate customers and internal teams on prompt engineering, LLM capabilities, and best practices for leveraging AI in their data operations
  • Build and extend internal tooling (importers, parsers, and reporting pipelines) to reduce manual burden on the Customer Experience team and improve platform reliability
  • Execute bespoke data operations such as custom SQL reports, bulk data operations, and backend queries for customers with unique data needs
  • Own API schemas, ingestion cadence, error handling, Snowflake data shares, and database connections
  • Identify repeatable patterns across customers and translate them into product requirements, filing tickets and partnering with Engineering to productize solutions
  • Support internal engineering workflows as a secondary function by helping to triage and resolve quality-of-life bugs and enhancements that are too small for core Engineering but directly impact the Customer Experience team and customers
  • Carry a light book of data parsing work alongside your teammates to stay grounded in the team's day-to-day workflows and build supporting solutions

Skills

  • 3–5+ years of experience in a technical role with a customer-facing component - solutions engineering, data engineering, technical account management, or similar
  • Strong SQL skills and ability to write complex queries, perform ad-hoc data analysis, and work with relational data models
  • Proficiency in Python for scripting, data manipulation, and workflow automation
  • Hands-on experience with REST APIs: designing, consuming, and debugging integrations
  • Willingness to travel up to 60% of the time to work on-site with customers
  • Familiarity with modern data infrastructure such as Snowflake, dbt, or similar data warehouse and pipeline tools
  • Strong communication and ability to translate technical concepts clearly for non-technical stakeholders
  • Experience in B2B SaaS, ideally in fintech, venture capital, or private markets
  • High ownership mentality. You identify problems proactively and drive solutions without waiting to be asked
  • Confidence operating in ambiguity. You don't need a fully defined playbook to get started, and you're energized rather than unsettled by the prospect of helping build one
  • Experience with prompt engineering, LLM-based workflows, or AI-forward tooling is a strong plus
  • Bonus: experience with data integration tools (Zapier, n8n, Make, or similar), exposure to fund accounting and investment data workflows, or experience configuring MCP servers and AI agents
  • Finance and/or Computer Science degree strongly preferred

Qualifications

Must Haves

  • 3–5+ years of experience in a technical role with a customer-facing component - solutions engineering, data engineering, technical account management, or similar
  • Strong SQL skills and ability to write complex queries, perform ad-hoc data analysis, and work with relational data models
  • Proficiency in Python for scripting, data manipulation, and workflow automation
  • Hands-on experience with REST APIs: designing, consuming, and debugging integrations
  • Willingness to travel up to 60% of the time to work on-site with customers
  • Familiarity with modern data infrastructure such as Snowflake, dbt, or similar data warehouse and pipeline tools
  • Strong communication and ability to translate technical concepts clearly for non-technical stakeholders
  • Experience in B2B SaaS, ideally in fintech, venture capital, or private markets
  • High ownership mentality. You identify problems proactively and drive solutions without waiting to be asked
  • Confidence operating in ambiguity. You don't need a fully defined playbook to get started, and you're energized rather than unsettled by the prospect of helping build one

Nice to Haves

  • Experience with prompt engineering, LLM-based workflows, or AI-forward tooling is a strong plus
  • Bonus: experience with data integration tools (Zapier, n8n, Make, or similar), exposure to fund accounting and investment data workflows, or experience configuring MCP servers and AI agents
  • Finance and/or Computer Science degree strongly preferred

Benefits

  • Health and dental insurance: We cover you and your dependents' medical/dental/vision insurance 100% in the USA. Internationally we match local health coverage for you and your family.
  • Flexible vacation: Take time off when you need it! We find most employees take 3-4 weeks in addition to holidays, but there are no firm rules. We trust our employees to know what's best for them.
  • Paid parental leave: 12 weeks of paid leave for all new parents in the USA. Internationally we match parental leave standards in your area.
  • Complete transparency: Everyone has full access to business metrics and financial information about the company.
  • Regular offsites: we fly the whole team out to an exciting destination to plan, bond, and innovate.

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