Data Solutions Engineer

Come Build With Us

The Data Solutions Engineer sits at the intersection of Customer Experience and Engineering at Standard Metrics. You'll be the dedicated technical owner for customer-facing data workflows, integrations, and AI-driven automation, while working across a book of customers to understand their data problems and build solutions that make Standard Metrics stickier and more impactful in their day-to-day workflows.

This is not a pure engineering role, and it's not a pure customer-facing role. You'll need both the technical depth to architect and execute solutions across APIs, SQL, data pipelines, and AI tooling, as well as the communication skills to work directly with customers to diagnose needs, set expectations, and deliver results. You'll be deeply embedded with our Data Solutions and Customer Success teams, acting as a technical extension of the customer.

This role is a foundational hire for a nascent services function at Standard Metrics. There's no established playbook here - you'll help write it. If you're energized by ambiguity, by the prospect of defining what "technical services" looks like for a product like ours, and by building something that didn't exist before, this is that opportunity.

What You’ll Do

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

What You’ll Bring

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

Genuine curiosity about AI. Experience with prompt engineering, LLM-based workflows, or AI-forward tooling is a strong plus

Willingness to travel 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

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