Job description

Senior Data Analyst Current is a leading consumer fintech platform transforming financial access for everyday Americans with over five million members. We provide access to financial solutions that seamlessly work together to solve the needs of our members and enable all Americans to build better financial futures. Based in NYC, our results-driven environment drives us to build better products, grow faster and empower everyone on our team to have an impact on our business and mission to improve financial outcomes. ABOUT THE ROLE We are looking for a Senior Data Analyst to play a central role in how we build, govern, and scale our analytics function. You will work closely with leadership and cross-functional teams to own data models, drive analytical initiatives, and ensure the business has reliable, well-defined data to make decisions from. This is a high-ownership role that sits at the intersection of data engineering rigour and business-facing analytics - suited to someone who is equally comfortable shaping a governance framework as they are presenting insight to a non-technical audience. RESPONSIBILITIES Own and evolve our core data models, ensuring the analytics layer accurately reflects business logic across the company’s unit economics model. Partner directly with leadership and cross-functional teams (Product, Engineering, Finance) to scope, prioritize, and deliver data-driven initiatives. Own data quality and reliability across the analytics platform - defining standards, implementing tests, and ensuring models are trustworthy before they reach consumers. Provide clear, actionable insight to stakeholders on business performance, customer behaviour, and metric trends - translating complex data into decisions. Take ownership of reconciliation workflows, cross-checking mart outputs against source systems and flagging discrepancies. Support the broader team with ad hoc analytics requests, with each task building domain context across Current’s metrics and business logic. Build and maintain dashboards, reports, and Looker explores that track KPIs across product, finance, and operations. ABOUT YOU 5+ years in a data analytics role where you owned multiple concurrent workstreams and operated with a high degree of autonomy. At least 2–3 years in a consumer-facing fintech, digital banking, payments, or lending environment, working closely with transactional data, product metrics, and customer behavior at scale. Proven track record of taking analytical projects from scoping through to delivery, with ownership over outcomes not just outputs. Strong written and verbal communication; comfortable presenting findings and recommendations to non-technical stakeholders and leadership. Technical proficiency across the modern data stack . Advanced SQL in a cloud data warehouse environment (Snowflake, BigQuery, or Redshift) - window functions, CTEs, and complex joins. Hands-on experience with dbt or a comparable transformation tool. Working knowledge of Looker or a comparable BI/semantic layer. Python for scripting and automation. Comfortable writing Python to manipulate data, flag anomalies, and automate repeatable analytical tasks. Additional Skills and Qualifications Familiarity with Unit Economics concepts - ARPU, contribution profit, cohort LTV, interchange - or experience working with transaction-level data at scale. Experience working in environments where data accuracy and auditability matter - validating outputs and tracing metric definitions across systems. Looker experience is ideal; any hands-on experience building explorers, views, or governed metric layers on top of a mart layer is valuable. Experience contributing to roadmaps, running cross-functional workstreams, or sitting alongside leadership in shaping how analytical work gets structured and prioritised - even informally. This role has a base salary range of $150,000-$200,000. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits. BENEFITS Competitive salary Meaningful equity in the form of stock options 401(k) plan Discretionary performance bonus program Biannual performance reviews Medical, Dental and Vision premiums covered at 100% for you and your dependents Flexible time off and paid holidays Generous parental leave policy Commuter benefits Fitness benefits Healthcare and Dependent care FSA benefit Employee Assistance Programs focused on mental health Healthcare advocacy program for all employees Access to mental health apps Team building activities Our modern NYC based office with open floor plan, stocked kitchen, and catered lunches

Requirements

Must-haves

Senior Data Analyst
Own and evolve our core data models, ensuring the analytics layer accurately reflects business logic across the company’s unit economics model.
Partner directly with leadership and cross-functional teams (Product, Engineering, Finance) to scope, prioritize, and deliver data-driven initiatives.
Own data quality and reliability across the analytics platform - defining standards, implementing tests, and ensuring models are trustworthy before they reach consumers.
Provide clear, actionable insight to stakeholders on business performance, customer behaviour, and metric trends - translating complex data into decisions.
Take ownership of reconciliation workflows, cross-checking mart outputs against source systems and flagging discrepancies.
Support the broader team with ad hoc analytics requests, with each task building domain context across Current’s metrics and business logic.
Build and maintain dashboards, reports, and Looker explores that track KPIs across product, finance, and operations.
5+ years in a data analytics role where you owned multiple concurrent workstreams and operated with a high degree of autonomy.
At least 2–3 years in a consumer-facing fintech, digital banking, payments, or lending environment, working closely with transactional data, product metrics, and customer behavior at scale.
Python for scripting and automation. Comfortable writing Python to manipulate data, flag anomalies, and automate repeatable analytical tasks.
Additional Skills and Qualifications
Familiarity with Unit Economics concepts - ARPU, contribution profit, cohort LTV, interchange - or experience working with transaction-level data at scale.
Experience working in environments where data accuracy and auditability matter - validating outputs and tracing metric definitions across systems.
Looker experience is ideal; any hands-on experience building explorers, views, or governed metric layers on top of a mart layer is valuable.
Experience contributing to roadmaps, running cross-functional workstreams, or sitting alongside leadership in shaping how analytical work gets structured and prioritised - even informally.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

sqlpython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Parental Leave