Senior Data Engineer

About Us:
DailyPay is transforming the way people get paid. As a worktech company and the industry’s leading on demand pay solution, DailyPay uses an award-winning technology platform to help America’s top employers build stronger relationships with their employees. This voluntary employee benefit enables workers everywhere to feel more motivated to work harder and stay longer on the job while supporting their financial well-being outside of the workplace.
DailyPay is headquartered in New York City, with operations throughout the United States as well as in Belfast. For more information, visit DailyPay's Press Center.

DailyPay is looking for a pragmatic Senior Data Engineer. Based in our New York office in a hybrid capacity and embedded within a distributed team, you will be at the heart of our mission, building data systems and business-critical pipelines that enable decisions right across the business. From financial compliance and operational insight to the intelligence that drives a better experience for our customers.

In this role, you will collaborate closely with Data, Engineering, Product and Finance colleagues, contributing to the evolution of our platform architecture while delivering new, high-impact data products.

If you are passionate about data and excited by the potential to make a real difference, not just for the teams you work with, but for the millions of customers who rely on DailyPay every day, then we want to hear from you!

• 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. Working closely with your team and the Senior Engineering Manager to identify and solve problems at the team level.

• 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.

• Data Engineering Experience: 6+ years of professional experience in Data Engineering, with a demonstrated track record of hands-on delivery and end-to-end ownership of scalable, high-quality data platforms.

• Modern Cloud Data Mastery: Deep, production-grade experience with Snowflake (strongly preferred) or comparable warehouses such as BigQuery or Databricks. You must have a strong command of the cost and performance implications of data design and query patterns.

• Expert SQL & dbt Skills: 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.

• Mentorship & Influence: Experience actively supporting the growth of others, with a proven ability to mentor peers and contribute to a healthy, collaborative engineering culture.

• End-to-End Ownership: A history of taking projects from initial ambiguity through to production, including CI/CD integration, automated testing, and ongoing data quality ownership.

• Clear Communication: The ability to articulate complex data concepts and technical trade-offs to both engineering peers and non-technical stakeholders.

• AI Readiness: A willingness to work with AI-assisted development tools as part of your daily workflow. You don't need to be an expert today, but you should be curious, open to learning, and able to critically evaluate AI-generated outputs before they reach production.

• Exceptional Communication: Strong ability to work closely with finance and non-technical stakeholders, translating complex business logic into clean, reusable datasets.

• Finance Domain Expertise: Experience working with highly regulated financial/accounting data, understanding financial modeling logic, or integrating ERP systems (e.g., NetSuite, Sage) to serve finance stakeholders.

• Data Activation Experience: Hands-on experience with reverse ETL tools (e.g., Hightouch, Census) to operationalize data and drive it back into business applications.

• Advanced Tooling Familiarity: Experience with orchestration tools (e.g., Airflow) and building Snowflake semantic views.

• Legacy Migration Experience: Proven ability to audit, understand, and migrate legacy reporting systems into a modern, structured data stack.

• Programming Skills: Familiarity with Python, Go, or Scala for custom data processing