Lead Revenue Data Engineer, Accounting & Close Automation

Paycom; Southlake (TX); Sur place; USD 140 000 - 180 000; Plein temps

Résumé du poste

Paycom is seeking a Lead Data Engineer, Revenue Accounting to design and operate automated revenue-recognition data products. You will build governed data pipelines on Azure/Snowflake, translating practice-management, billing, and GL data into auditable revenue outputs.

The role combines engineering, data modeling, and close-cycle support, collaborating with Finance, Revenue Cycle, and technology to improve timing, accuracy, and scalability of revenue data assets.

Qualifications

• Bachelor’s degree in a related field or equivalent experience.
• 8+ years data engineering, analytics or warehousing experience.
• 3+ years leading complex technical deliveries or teams.
• Strong SQL and Python, with production data-pipeline experience.
• Experience with Snowflake and Azure in ELT/ETL environments.

Responsabilités

• Own the technical roadmap and delivery plan for the Revenue Recognition Data Product.
• Architect scalable ingestion, transformation, and orchestration pipelines using Azure and Snowflake.
• Develop a canonical revenue-accounting data model with controller ownership preserved by Accounting.
• Establish automated reconciliations across source systems and the general ledger.
• Build data controls, lineage, and runbooks for close processes and auditability.

Connaissances

SQL

Python

Data modeling

Stakeholder management

Communications

Formation

Bachelor's degree in computer science, information systems, engineering, accounting, finance, or related

Outils

Snowflake

Azure

dbt

Azure Data Factory

Azure Databricks

Terraform

Airflow

CI/CD tools

Description du poste

Paycom is seeking a Lead Data Engineer, Revenue Accounting to design and operate automated revenue-recognition data products. You will build governed data pipelines on Azure/Snowflake, translating practice-management, billing, and GL data into auditable revenue outputs.

The role combines engineering, data modeling, and close-cycle support, collaborating with Finance, Revenue Cycle, and technology to improve timing, accuracy, and scalability of revenue data assets.