Data Engineer II

DailyPay•New York, NY

4d•$120,000 - $140,000

About The Position

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.

Requirements

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

Responsibilities

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