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About the job

Senior Data Engineer

About Beacon Behavioral Health

Beacon Behavioral Health is a fast-growing behavioral healthcare organization with a mission to expand access to high-quality mental health services and improve outcomes for the patients and communities we serve. As Beacon continues to grow organically and through acquisitions, building a trusted and scalable data foundation is critical to improving clinical care, operations, decision-making, and innovation.

Position Overview

Beacon is seeking a Senior Data Engineer to help build and scale our enterprise data platform. This role will be responsible for designing, building, and maintaining the data warehouse, data pipelines, integrations, and infrastructure that power analytics, reporting, automation, and AI initiatives across the organization.

The ideal candidate is a hands-on data engineer with strong experience building modern cloud data platforms and integrating data from complex source systems. Healthcare data experience is strongly preferred, particularly experience working with EHR, clinical, revenue cycle, payer, or patient data.

Key Responsibilities

Design, build, and maintain Beacon's enterprise data warehouse and supporting data architecture.

Develop reliable and scalable data pipelines integrating data from EHRs, practice management systems, revenue cycle platforms, APIs, databases, and other enterprise applications.

Build and maintain cloud-based data infrastructure primarily within AWS.

Create standardized and trusted data models for clinical, operational, financial, and executive reporting.

Build data integration capabilities to support Beacon's growing portfolio of practices and acquired organizations.

Partner with business and technology teams to translate reporting and analytics requirements into scalable data solutions.

Establish data quality, validation, monitoring, lineage, and documentation practices.

Optimize data pipelines and warehouse performance, reliability, and cost.

Develop APIs, data services, and reusable datasets to support applications, automation, analytics, and AI use cases.

Help establish enterprise data engineering standards, architecture, and development best practices.

Ensure healthcare data is handled securely and in accordance with HIPAA and organizational security requirements.

Qualifications

5+ years of professional experience in data engineering or related roles.

Strong experience designing and building cloud-based data warehouses and modern data platforms.

Strong hands-on experience with AWS and AWS data services.

Advanced proficiency with SQL and Python.

Strong experience building ETL/ELT pipelines and integrating data from APIs, databases, files, and third-party platforms.

Experience with data modeling, dimensional modeling, data quality, and pipeline orchestration.

Experience building and maintaining production-grade data pipelines and cloud data infrastructure.

Understanding of data governance, security, access controls, and sensitive data management.

Strong problem-solving skills and ability to work independently in a fast-growing environment.

Excellent collaboration and communication skills.

Preferred Qualifications

Healthcare data engineering experience strongly preferred.

Experience working with EHR/EMR, clinical, claims, billing, eligibility, or revenue cycle data.

Understanding of healthcare data standards such as HL7, FHIR, X12, ICD-10, CPT, and related healthcare data models.

Experience extracting data from healthcare systems using APIs, database access, HL7 feeds, or other integration methods.

Experience with Tableau is a plus.

Experience integrating data following healthcare acquisitions or across multiple EHR and practice management systems.

Ideal Candidate

We are looking for a hands-on senior engineer who enjoys building the data foundation, not simply maintaining an existing environment. This individual will help Beacon turn data distributed across clinical and business systems into a trusted enterprise asset that enables better reporting, operational insights, automation, and AI as the organization continues to scale.