Analytics Engineer, Finance

EvenUp

. Enable the Finance team by providing documented, auditable, trusted tables that analysts and AI-assisted workflows can use without engineering support .

Posted 11/12/2026full-timeRemote • United StatesMid-LevelSenior💰 $160,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and managing finance data warehouses on Google Cloud, with a strong focus on data modeling, PHI de-identification, and compliance with legal standards. Proficient in SQL, dbt, and cloud data warehouse technologies to enable finance teams with reliable, auditable data solutions.

Highest-signal resume keywords

Google Cloud BigQuerySQL Data ModelingDbt ExperiencePHI De-identificationFinance Data Warehouse Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringData Warehouse DevelopmentData ModelingPHI IdentificationTokenizationFree-Text RedactionIAM Security ControlsGit Version ControlPython ProgrammingMedallion Architecture

Soft Skills

Independent WorkCuriosityRoot-Cause AnalysisStakeholder CommunicationTechnical Tradeoff Explanation

Tools & Technologies

Google Cloud DLPSalesforceStripeMetabaseAgentic Coding Tools

Industry Keywords

FinanceAccountingRevenue OperationsHIPAA ComplianceLegal TechHealthcareRegulated Industry

Tech Stack

Tools & technologies

BigQueryCloudERPPythonSQL

About the role

Key responsibilities & impact

Enable the Finance team by providing documented, auditable, trusted tables that analysts and AI-assisted workflows can use without engineering support
Design and build the Finance warehouse on Google Cloud (BigQuery), including environments, access controls, cost management, and documentation
Own PHI identification and removal by inventorying source columns, classifying them, and building the scrubbing layer, including field-level removal, tokenization, and free-text redaction
Define data specifications and partner cross-functionally with Analytics to ingest and incorporate necessary data feeds
Define and operate controls in partnership with Legal and Security to set the de-identification standard and automate checks for PHI leakage
Build finance data models in dbt, including recognized revenue, billings, cash collections, CARR bridge, and credit consumption
Reconcile and validate warehouse outputs against Salesforce, Stripe, and the general ledger
Transition existing finance workstreams and models from shared warehouse datasets to the new Finance-owned environment
Complete the source and PHI inventory, agree the de-identification standard with Legal and Security, and finalize the warehouse architecture and project plan within the first 90 days
Land core finance sources in the warehouse with automated PHI checks passing and deliver a first set of validated finance models within the first 6 months
Transition Finance reporting to the Finance-owned warehouse, reconcile recognized revenue and cash models to the ledger, and enable Finance self-service within the first 12 months

Requirements

What you’ll need

5+ years of data engineering, including at least one data warehouse built from scratch, ideally in finance at a pre-IPO company
Experience supporting finance, accounting, or revenue operations teams
Strong SQL, hands-on data modeling, and dbt experience, with familiarity with medallion architecture
Hands-on experience with BigQuery or comparable cloud data warehouse, including IAM, security controls, and policy tags
Experience de-identifying or restricting access to sensitive data (PHI, PII, financial data) and working knowledge of HIPAA de-identification methods
Experience building tested, documented dbt models that enable analyst self-sufficiency
Comfort partnering with Legal, Security, and Finance stakeholders to explain technical tradeoffs
Ability to work independently with no existing playbook; innate curiosity and root-cause analysis skills
Proficiency with software engineering best practices, including Git version control
Agentic coding tools (e.g., Claude Code, Cursor, Codex) are part of your regular workflow, and you verify and take ownership of AI-generated output
Experience building, shipping, evaluating, and monitoring LLM or agent systems in production
Google Cloud Sensitive Data Protection (DLP) or similar redaction tooling
Familiarity with Salesforce data models, Stripe billing data, or an ERP such as NetSuite
Experience with Metabase or similar BI tools
Python experience
Background in legal tech, healthcare, or another regulated industry

Benefits

Comp & perks

Choice of medical, dental, and vision insurance plans for you and your family.
Additional insurance coverage options for life, accident, or critical illness.
Flexible paid time off, sick leave, short-term and long-term disability.
10 US observed holidays, and Canadian statutory holidays by province.
A home office stipend.
401(k) for US-based employees and RRSP for Canada-based employees.
Paid parental leave.
A local in-person meet-up program.
Equity