Senior Data Engineer

DailyPay

Senior Data Engineer at DailyPay, building data systems and pipelines for business-critical decisions. Collaborating with teams to enhance data platform architecture and develop high-impact products.

Posted 6/15/2026full-timeNew York City • New York • 🇺🇸 United StatesSenior💰 $158,000 - $209,000 per yearWebsite

Tech Stack

Tools & technologies

BigQuerySQL

About the role

Key responsibilities & impact

Architect and Evolve our Data Platform: You will design and deliver end-to-end data models and pipelines that power critical business decisions, defining project scopes, unblocking dependencies, and ensuring our data layer remains reliable and extensible as we scale.
Optimize for Performance and Cost: You will proactively identify and resolve performance bottlenecks across high-volume data workflows, taking ownership of query design, data scanning, and warehouse usage to keep our data platform lean, resilient, and built to scale.
Align Data with Mission: You will serve as a bridge between technical solutions and business needs. Translating complex business logic into clean, reusable datasets and driving the creation of new, high-value data products that empower users across the organization.
Champion Data Engineering Excellence: You will lead code reviews with a security-first lens, drive rigorous testing standards, and mentor peers with empathy to build team redundancy and shared capability.
Support Architectural Modernization: You will contribute to DailyPay's transition from a monolithic to a micro-services architecture, ensuring affected pipelines are re-engineered for robustness, scalability, and long-term maintainability.
Innovate with AI: You will champion the use of AI to develop more performant systems, improve proactive alerting, and design data products that enable data-driven decision-making across DailyPay.
Participate in On-Call: You will join an on-call rotation, responding to production incidents and contributing to blameless post-mortems that strengthen our systems over time.

Requirements

What you’ll need

6+ years of professional experience in Data Engineering
Deep, production-grade experience with Snowflake (strongly preferred) or comparable warehouses such as BigQuery or Databricks
Advanced SQL capabilities for writing and optimizing complex queries, paired with extensive hands-on experience in data transformation, dimensional modeling, and implementing quality checks and testing frameworks in dbt
Experience actively supporting the growth of others, with a proven ability to mentor peers and contribute to a healthy, collaborative engineering culture
A history of taking projects from initial ambiguity through to production, including CI/CD integration, automated testing, and ongoing data quality ownership
The ability to articulate complex data concepts and technical trade-offs to both engineering peers and non-technical stakeholders
A willingness to work with AI-assisted development tools as part of your daily workflow
Strong ability to work closely with finance and non-technical stakeholders, translating complex business logic into clean, reusable datasets

Benefits

Comp & perks

Exceptional health, vision, and dental care
Opportunity for equity ownership
Life and AD&D, short- and long-term disability
Employee Assistance Program
Employee Resource Groups
Fun company outings and events
Unlimited PTO
401K with company match

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Data EngineeringSnowflakeBigQueryDatabricksSQLdata transformationdimensional modelingdbtCI/CDautomated testing

Soft Skills

mentoringcollaborationcommunicationproblem-solvingleadershipempathyproject managementadaptabilitytechnical translationstakeholder engagement