Lead Data Engineer (33002)

GI Alliance; Southlake (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

GI Alliance is seeking a Lead Data Engineer to design, deliver, and operate an automated revenue-recognition and accrual data product for a physician-led MSO model. You will build governed data pipelines on Azure and Snowflake, turning practice-management, billing, and GL data into timely outputs.

You will standardize revenue recognition, improve controls and auditability, mentor engineers, and collaborate with Finance, Accounting, and Revenue Cycle to shorten close timelines and reduce manual

Qualifications

• 8+ years of data engineering, analytics engineering, data warehousing, or related experience.
• 3+ years leading complex technical deliveries, technical workstreams, or other engineers.
• Demonstrated experience building production data pipelines and curated data models using Snowflake and Azure.
• Strong SQL and Python skills, including transformation logic, testing, troubleshooting, and performance tuning.
• Experience with modern ELT/ETL, orchestration, CI/CD, Git-based development, automated testing, and production monitoring.
• Experience integrating heterogeneous financial, operational, billing, ERP, practice-management, or RCM systems.
• Ability to translate complex business and accounting concepts into maintainable, testable data logic.
• Strong stakeholder-management and written-communication skills, with the ability to work effectively with Accounting, Finance, auditors, revenue-cycle operators, and engineers.

Responsibilities

• Own the technical roadmap and delivery plan for the Revenue Recognition Data Product, including source onboarding, data quality, reconciliation, controls, and production support.
• Architect and build scalable ingestion, transformation, and orchestration pipelines using Azure services and Snowflake.
• Develop a canonical revenue-accounting data model that standardizes charges, payments, adjustments, contractual allowances, refunds, credit balances, unapplied cash, denials, reserves, accruals, and journal-entry support.
• Translate accounting requirements and revenue-recognition policy into transparent, version-controlled transformation logic, while Accounting retains policy ownership and final close approval.
• Establish automated reconciliations among source systems, subledgers, RCM platforms, data-product outputs, and the general ledger, with documented exception-management workflows.
• Build data controls for completeness, accuracy, timeliness, uniqueness, lineage, change management, and period-close signoff.
• Produce auditable documentation, including source-to-target mappings, business rules, control evidence, lineage, data dictionaries, runbooks, and release records.
• Partner with Finance and Revenue Cycle leaders to define close-calendar milestones, materiality thresholds, approval points, and service-level expectations.
• Lead technical discovery and onboarding for multiple practice groups and acquired entities, balancing enterprise standardization with local-system variation.
• Implement observability and support practices, including monitoring, alerting, incident response, root-cause analysis, and post-close validation.
• Establish reusable engineering standards for SQL, Python, Git-based development, CI/CD, testing, infrastructure-as-code, security, and peer review.
• Mentor engineers and provide technical leadership for future revenue-accounting engineering workstreams.
• Communicate clearly with technical and nontechnical stakeholders, including reconciliation results, delivery status, risks, decisions needed, and realized value.

Skills

Leadership

Communication

SQL

Python

Data modeling

Education

Bachelor's degree in CS/IS/Engineering

Tools

Snowflake

Azure

dbt

Azure Data Factory

Airflow

Terraform

Git CI/CD

Job description

Company Conformance Statements

In the performance of their respective tasks and duties all employees are expected to conform to the following:

• Perform quality work within deadlines with or without direct supervision.
• Interact professionally with other employees, customers and suppliers.
• Work effectively as a senior contributor on all projects.
• Work independently while understanding the necessity for communicating and coordinating team efforts with departments and organizations.

Company Conformance Statements

In the performance of their respective tasks and duties all employees are expected to conform to the following:

• Perform quality work within deadlines with or without direct supervision.
• Interact professionally with other employees, customers and suppliers.
• Work effectively as a senior contributor on all projects.
• Work independently while understanding the necessity for communicating and coordinating team efforts with departments and organizations.

Position purpose

The Lead Data Engineer will lead the design, delivery, and operation of The Specialty Alliance’s automated revenue-recognition and accrual data product. The role is designed to support a physician-led, multi-specialty MSO model that provides shared infrastructure, analytics, contracting, compliance, and revenue-cycle support while preserving practice-level clinical autonomy.

This leader will build governed data pipelines and reconciliation-ready accounting datasets on Azure/Snowflake, translating source-system activity such as practice-management, billing, RCM, contractual, and general-ledger data into timely, traceable, and explainable revenue and accrual outputs. The position combines hands-on engineering, financial controls design, data modeling, and close-cycle delivery support.

The primary purpose of the role is to standardize and automate revenue recognition and accrual processes across affiliated practices while improving control, transparency, auditability, and scalability. The successful candidate will partner with Finance, Accounting, Revenue Cycle, and technology teams to reduce manual work, shorten close timelines, improve reconciliation quality, and create durable financial-data assets.

Responsibilities/Duties/Functions/Tasks

• Own the technical roadmap and delivery plan for the Revenue Recognition Data Product, including source onboarding, data quality, reconciliation, controls, and production support.
• Architect and build scalable ingestion, transformation, and orchestration pipelines using Azure services and Snowflake.
• Develop a canonical revenue-accounting data model that standardizes charges, payments, adjustments, contractual allowances, refunds, credit balances, unapplied cash, denials, reserves, accruals, and journal-entry support.
• Translate accounting requirements and revenue-recognition policy into transparent, version-controlled transformation logic, while Accounting retains policy ownership and final close approval.
• Establish automated reconciliations among source systems, subledgers, RCM platforms, data-product outputs, and the general ledger, with documented exception-management workflows.
• Build data controls for completeness, accuracy, timeliness, uniqueness, lineage, change management, and period-close signoff.
• Produce auditable documentation, including source-to-target mappings, business rules, control evidence, lineage, data dictionaries, runbooks, and release records.
• Partner with Finance and Revenue Cycle leaders to define close-calendar milestones, materiality thresholds, approval points, and service-level expectations.
• Lead technical discovery and onboarding for multiple practice groups and acquired entities, balancing enterprise standardization with local-system variation.
• Implement observability and support practices, including monitoring, alerting, incident response, root-cause analysis, and post-close validation.
• Establish reusable engineering standards for SQL, Python, Git-based development, CI/CD, testing, infrastructure-as-code, security, and peer review.
• Mentor engineers and provide technical leadership for future revenue-accounting engineering workstreams.
• Communicate clearly with technical and nontechnical stakeholders, including reconciliation results, delivery status, risks, decisions needed, and realized value.

Qualifications

• Bachelor’s degree in computer science, information systems, engineering, accounting, finance, or a related discipline; equivalent practical experience considered.
• 8+ years of data engineering, analytics engineering, data warehousing, or related experience.
• 3+ years leading complex technical deliveries, technical workstreams, or other engineers.
• Demonstrated experience building production data pipelines and curated data models using Snowflake and Azure.
• Strong SQL and Python skills, including transformation logic, testing, troubleshooting, and performance tuning.
• Experience with modern ELT/ETL, orchestration, CI/CD, Git-based development, automated testing, and production monitoring.
• Experience integrating heterogeneous financial, operational, billing, ERP, practice-management, or RCM systems.
• Strong understanding of data modeling, reconciliation design, data quality, lineage, metadata, security, and operational support.
• Ability to translate complex business and accounting concepts into maintainable, testable data logic.
• Strong stakeholder-management and written-communication skills, with the ability to work effectively with Accounting, Finance, auditors, revenue-cycle operators, and engineers.

Preferred Qualifications

• Healthcare-provider, MSO, physician-practice, payer, or revenue-cycle experience.
• Direct experience supporting revenue recognition, accruals, month-end close, GL interfaces, accounting reserves, or financial controls.
• Familiarity with healthcare-revenue concepts such as charge capture, remittances, contractual adjustments, denial trends, refunds, patient balances, and AR aging.
• Experience with dbt, Azure Data Factory, Azure Databricks, Azure DevOps, Terraform, Airflow, or comparable tooling.
• Knowledge of healthcare privacy and security obligations, including HIPAA-aligned data handling.
• CPA, CMA, accounting degree, or meaningful partnership experience with controllership and audit stakeholders.
• Experience in M&A, multi-entity consolidation, practice onboarding, or system conversion work.
• Self-managed or need little supervision
• Persistence in staying on task to solve technical problems
• Flexibility and initiative
• Accountability for own schedule and reporting on activities
• Conceptual thinking
• This role routinely uses standard office equipment such as computers, phones, and fax machines.