Data Engineer II
Data Engineer · Mid · Full Time
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Role
What you'll do.
Data Engineer II at DailyPay is a mid-level role focused on designing and maintaining robust data infrastructure, ETL pipelines, and analytics systems that serve cross-functional teams and partner companies. You'll optimize data warehouse performance, implement data quality frameworks, and collaborate on scalable solutions for a fintech platform transforming employee financial wellness. This position requires 4+ years of SQL expertise, cloud platform experience, and knowledge of modern data warehousing solutions like Snowflake or BigQuery.
Responsibilities
- Build and Maintain ETL Pipelines: Design, develop, and optimize extraction, transformation, and loading (ETL) processes that reliably move data from various internal and external sources into DailyPay's data infrastructure. Ensure pipelines handle large volumes of payroll and financial data with high reliability and minimal latency.
- Implement Data Testing and Scaling Capabilities: Establish robust data validation frameworks and implement testing methodologies to ensure data quality across pipelines. Design and implement solutions that scale efficiently as data volumes grow, maintaining performance and cost-effectiveness in the data warehouse.
- Monitor and Optimize Infrastructure: Maintain comprehensive monitoring and alerting systems for ETL processes, data warehouses, and analytics infrastructure. Proactively identify bottlenecks, optimize query performance, and reduce warehouse operational costs while improving development velocity.
- Database Performance Optimization: Analyze and optimize database queries, indexing strategies, and data storage architectures to improve system performance. Focus on reducing warehouse costs and minimizing development timelines through architectural improvements and query optimization.
- Code Review and Analytics Engineering: Participate actively in peer code reviews and pull request approvals for company-wide analytics engineering efforts. Provide technical feedback to ensure code quality, maintainability, and adherence to data engineering best practices across teams.
- Support Reporting and Analytics: Produce, maintain, and support data reports, metrics, and interactive dashboards used by internal departments (finance, sales, marketing, operations, engineering) and external DailyPay partner companies. Ensure accuracy and accessibility of analytics products for diverse stakeholder needs.
Qualifications
What we look for.
Technical
Advanced SQL Expertise
4+ years of professional SQL experience with expert-level capability in complex query optimization, window functions, CTEs, and performance tuning across various database systems.
Data Storage Architecture Knowledge
Demonstrated experience designing and implementing modern data storage solutions including dimensional models, data lakes, lakehouses, and data warehouses. Understanding of schema design patterns and their tradeoffs for analytics workloads.
Event-Driven Architecture and Cloud Platforms
Hands-on experience working with event-driven data architectures and cloud platforms such as AWS, Azure, or GCP. Familiarity with cloud-native data services and distributed systems concepts.
Large-Scale Data Processing
Proven ability to work with high-volume datasets, designing performant and scalable data models. Experience with distributed computing concepts and optimization techniques for analytical queries at scale.
MPP Data Warehouse Platforms
Professional experience with massively parallel processing data warehouses such as Snowflake, BigQuery, Redshift, or similar platforms. Understanding of their unique optimization techniques and cost management strategies.
ETL Tool Proficiency
Hands-on experience with modern ETL tools such as Fivetran, Stitch, or equivalent platforms for data integration and pipeline automation.
Business Intelligence Tools
Familiarity with BI platforms such as Tableau, Looker, Power BI, or similar tools for creating visualizations and dashboards that communicate data insights effectively.
Education
Bachelor's Degree (Preferred)
Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related field. Equivalent professional experience demonstrating strong foundational technical knowledge is acceptable.
Experience
4+ Years Data Engineering or Analytics Engineering
Minimum 4+ years of professional experience in data engineering, analytics engineering, or closely related roles involving SQL, data pipeline development, and data warehouse management.
Legacy System Modernization
Demonstrated ability to reverse-engineer legacy reporting systems and rebuild them into structured, maintainable, and automated solutions using modern data engineering practices.
Cross-Functional Communication
Proven track record of explaining complex technical data concepts to non-technical stakeholders including finance, operations, and business partners. Strong ability to translate business requirements into technical solutions.
Skills
Required
SQL
Expert-level SQL proficiency for complex query development, performance optimization, and database design in production data warehousing environments.
Data Warehousing
Deep understanding of modern data warehouse platforms, dimensional modeling, and optimization strategies for analytical queries at enterprise scale.
ETL/ELT Pipeline Development
Proficiency in designing and implementing data pipelines using contemporary tools and methodologies, with focus on reliability, performance, and maintainability.
Cloud Platforms
Hands-on experience with major cloud providers (AWS, Azure, or GCP) and their data services for building scalable data infrastructure.
Data Modeling
Ability to design efficient data models including dimensional models, entity-relationship schemas, and data lake architectures appropriate for analytical workloads.
Performance Optimization
Expertise in identifying and resolving performance bottlenecks through query optimization, indexing strategies, and infrastructure tuning.
Preferred
Python or Go
Nice to haveExperience with Python, Go, or similar programming languages for custom data processing, automation scripts, and system integration tasks.
dbt (Data Build Tool)
Nice to have1+ years of professional experience with dbt, including implementing data quality checks, version control integration, and establishing testing frameworks for analytics code.
Financial and ERP Systems
Nice to haveExperience working with financial data, accounting systems, or enterprise resource planning (ERP) platforms such as NetSuite, Sage, or similar solutions.
CI/CD and Orchestration
Nice to haveFamiliarity with continuous integration/continuous deployment practices, automated release processes, and orchestration tools such as Apache Airflow or Prefect.
Reverse ETL
Nice to haveExperience with reverse ETL tools and platforms such as Hightouch or Census for activating data warehouse insights by pushing processed data back into operational business applications.
Artificial Intelligence Integration
Nice to haveInterest in leveraging machine learning and AI capabilities to develop more efficient data systems, improve anomaly detection and proactive alerting mechanisms, and optimize query performance.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 120,000 – 140,000
Equity·Stock options
Benefits
Comprehensive Health Coverage
Exceptional health, vision, and dental insurance plans with competitive coverage and low out-of-pocket costs for employees and their families.
Equity Ownership Opportunity
Opportunity to own equity in DailyPay as part of competitive compensation, aligning your success with company growth and long-term value creation.
Disability and Life Protection
Life insurance, accidental death and dismemberment (AD&D) coverage, plus short-term and long-term disability protection to safeguard your financial security.
Employee Assistance Program
Confidential support services including counseling, financial planning, and legal consultation to help you navigate personal and professional challenges.
Employee Resource Groups
Active community groups providing networking, professional development, and cultural celebration for employees from diverse backgrounds and experiences.
Flexible Time Off
Unlimited paid time off policy enabling you to balance work and personal priorities, with encouragement to take meaningful time away.
Retirement Planning
401(k) retirement savings plan with company matching contributions to help you build long-term financial security.
Company Events and Culture
Regular fun company outings and team events fostering community connections and celebrating collective achievements across DailyPay.
Process
Interview steps.
- 01
Application and Resume Review
Initial screening of your application materials to assess alignment with technical requirements and experience level.
- 02
Recruiter Phone Screen
Introductory conversation with DailyPay's recruiting team to discuss your background, career goals, and interest in the Data Engineer II role.
- 03
Technical Assessment or Take-Home Challenge
SQL and data modeling assessment demonstrating expertise in query optimization, schema design, and analytical thinking. May involve analyzing real-world data problems or optimizing existing queries.
- 04
Data Engineering Manager Interview
In-depth technical discussion with the Data Engineering Manager covering architecture decisions, experience with data warehousing platforms, ETL pipeline design, and problem-solving approach.
- 05
Team Technical Interview
Collaborative session with members of the Data Engineering team discussing technical challenges, code review practices, and cultural fit through scenario-based questions.
- 06
Stakeholder or Leadership Interview
Meeting with cross-functional stakeholders (finance, analytics, or operations leaders) to assess communication skills, ability to translate business needs into technical solutions, and cross-team collaboration capabilities.
- 07
Offer and Negotiation
Compensation discussion, benefits review, and finalization of employment terms following successful completion of interview rounds.
Full posting
Original listing.
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.
The Role:
DailyPay is looking for a Data Engineer II to join our Data Engineering Team. The Data Engineering Team is responsible for building the data infrastructure that underpins our data analytics and data products that are used cross-functionally inside the company (finance, sales, marketing, operations, engineering, etc.) as well as by DailyPay partner companies. The team also ingests internal and external data to help provide insights about the payroll industry in general, as well as about personal finance and financial wellbeing.
How You Will Make an Impact:
Build and maintain company’s ETL and data pipelines
Design and implement data testing and scaling capabilities
Maintain and optimize monitoring and alerting for company’s ETL and data pipelines, data warehouse, and analytics infrastructure
Optimize database performance while reducing warehouse costs and development times
Participate in code approvals and PR review process for company-wide analytics engineering efforts
Produce, support and maintain data reports, analytics, metrics and dashboards for internal and external use
What You Bring to The Team:
4+ years SQL experience; expert SQL capability
Interest in utilizing AI to develop more efficient systems, improve proactive alerting, and optimize query performance
Experience in data storage architectures, including dimensional models, data lakes, data lakehouses, and data warehouses
Experience working in an event-driven architecture and cloud platforms (e.g. AWS, Azure, GCP)
Experience working with large volumes of data, making models performant and scalable
Familiarity with BI tools (e.g Tableau, Looker, or similar)
Excellent presentation and communication skills
Experience with MPP data warehouses, such as Snowflake or BigQuery.
Familiarity with ETL tools, such as Fivetran or Stitch
Ability to reverse-engineer legacy reports and rebuild them into structured, automated solutions
Excellent skills in explaining technical data concepts to non-technical finance and operations partners
Nice to Haves:
Familiarity with Python, Go, or similar languages for custom data processing and automation
1+ years of experience with dbt (Data Build Tool), including implementing data quality checks and testing frameworks
Experience working with financial/accounting data or platforms such as NetSuite, Sage, or similar ERP systems
Experience with CI/CD, automated releases, and orchestration tools like Airflow
Familiarity with reverse ETL tools (e.g., Hightouch or Census) to push data from the warehouse into business applications
What We Offer:
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
High-performing cultures aren't built in silos, they thrive on partnership. At DailyPay, we Commit Together to an inclusive, professional environment where multifaceted perspectives are our greatest competitive advantage. We recognize that our team members don’t live “single-issue lives,” and we lean into the wide-ranging backgrounds and life stages that sharpen our collective decision-making.
In our high-trust environment, we empower you to Challenge Norms. We’ve created a space where it is safe to ask difficult questions, disrupt the status quo, and share bold perspectives without fear of professional fallout. We believe that by checking our own assumptions and staying curious about the experiences of others, we arrive at better, more innovative results.
We provide the space for you to do your best work through peer advocacy and transparent career development. If you are looking for a culture that values intellectual honesty, celebrates the unique lived experiences of its people, and thrives on collective success, you’ll find it here.
If you require reasonable accommodation for any aspect of the recruitment process, please send a request to [email protected]. All requests for accommodation will be addressed as confidentially as practicable.
DailyPay is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion or creed, alienage or citizenship status, political affiliation, marital or partnership status, age, national origin, ancestry, physical or mental disability, medical condition, veteran status, gender, gender identity, pregnancy, childbirth (or related medical conditions), sex, sexual orientation, sexual and other reproductive health decisions, genetic disorder, genetic predisposition, carrier status, military status, familial status, or domestic violence victim status and any other basis protected under federal, state, or local laws.
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