Data Engineer II

Data Engineer · Mid · Full Time

NYC HeadquartersUSD 120k – 140k4d ago
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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 have

    Experience with Python, Go, or similar programming languages for custom data processing, automation scripts, and system integration tasks.

  • dbt (Data Build Tool)

    Nice to have

    1+ 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 have

    Experience 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 have

    Familiarity with continuous integration/continuous deployment practices, automated release processes, and orchestration tools such as Apache Airflow or Prefect.

  • Reverse ETL

    Nice to have

    Experience 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 have

    Interest 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

SQLPythonGo

Frameworks

dbt (Data Build Tool)Apache Airflow

Databases

SnowflakeBigQueryAWS Data ServicesAzure Data Services

Tools

FivetranStitchTableauLookerHightouchCensus

Other

Event-Driven ArchitectureData Lake ArchitectureData Quality FrameworksMonitoring and Alerting Systems

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.

  1. 01

    Application and Resume Review

    Initial screening of your application materials to assess alignment with technical requirements and experience level.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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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