Sr. Manager Data Engineering

The Senior Manager, Data Engineering, leads the organization’s data engineering function, including data integration,database development, and data cleansing and mapping. This hands-on management role is accountable for managing a data platform that serves as a trusted foundation for reporting, analytics, and AI initiatives.
The role manages onshore Data Engineers, directs offshore and vendor resources, and partners closely with the Senior Manager, Reporting and Analytics, and with business units such as Billing, Clinical Operations, Finance, Accounting,Human Resources, and Security & Compliance.

• Lead the team across onshore, offshore, and vendor resources by setting priorities, managing backlog and capacity, assigning work, and holding the team and vendors accountable for delivery commitments.
• Manage onshore Data Engineers, including recruiting, onboarding, goal setting, coaching, performance reviews,and development planning.
• Stay hands-on in complex or high-impact work, guiding the team on source systems, integration logic, data models, and transformations.
• Oversee the design, development, and support of ETL/ELT pipelines, interfaces, and file-based feeds that acquire, cleanse, map, and deliver data from internal and external sources.
• Own the maintenance and governance of billing rules and related business logic, ensuring changes are documented, tested, validated with business owners, and approved.
• Establish and enforce standards for development, data modeling, code review, testing, change and version control, deployment, and documentation across the data delivery lifecycle.
• Drive data quality and integrity through validation, reconciliation, monitoring, and exception-handling processes.
• Maintain a data catalog covering sources, integrations, business definitions, mappings, lineage, dependencies,load schedules, and support ownership.
• Oversee the health of the SQL Server environment, including performance, capacity, job scheduling, monitoring,and backup and recovery, partnering with infrastructure resources as needed.
• Protect PHI and PII through appropriate access controls, encryption, auditing, and adherence to HIPAA and organizational security policies.
• Lead response to production issues, such as failed loads, integration errors, and data discrepancies, through root-cause analysis, remediation, and prevention.
• Partner with the Reporting and Analytics team and business stakeholders to gather requirements, flag inconsistencies, and deliver data that supports accurate and timely reporting.
• Reduce dependency on individual subject-matter experts through documentation, cross-training, and reusable solutions.
• Introduce automation and AI-enabled approaches, such as AI-assisted data extraction, mapping, and validation,with appropriate controls for accuracy and security.
• Represent Data Engineering in planning, governance, architecture, and vendor discussions, and recommend platform, tool, and practice improvements based on business priorities.

• 7+ years of progressive experience in database development, data engineering, or data integration.
• 4+ years of experience in healthcare, supporting revenue cycle, billing, clinical, or financial data needs.
• 3+ years of experience leading data engineering teams, including offshore or vendor-supported resources.
• Strong hands-on experience with SQL Server, including T-SQL development, data modeling, performance tuning,and database architecture.
• Strong experience designing and supporting data integration using Azure Data Factory.
• Experience establishing disciplined SDLC, change-control, release, and production-support processes.
• Demonstrated ability to improve data governance, quality, and reliability.
• Working knowledge of HIPAA and safeguards for PHI and other sensitive data.
• Strong communication skills with business stakeholders, and ability to manage multiple priorities.
• Bachelor's degree or higher; equivalent relevant experience may be considered.

Preferred Experience:

• Experience integrating healthcare EDI data, such as 835 and 837 files.
• Experience extracting data from documents using AI/LLM-based tools.

NOTE: This position follows a hybrid work model with a minimum of 2-3 days per week in our Addison, TX office

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