Senior Data Engineer

Advanced Medical Management•Long Beach, CA

14d•$150,000 - $180,000

About The Position

The Senior Data Engineer is responsible for the ownership, design, development, optimization, and ongoing support of the organization's enterprise data platform. This role serves as the primary technical owner of the Snowflake data warehouse, dbt transformation framework, and supporting data engineering ecosystem, ensuring the integrity, quality, availability, reliability, and scalability of enterprise data assets that support reporting, analytics, and operational decision-making. This individual partners closely with business stakeholders, Business Intelligence developers, application owners, data support teams, and IT leadership to design and maintain scalable data solutions, integrate data from multiple operational systems, and transform raw data into trusted business information. The Senior Data Engineer is responsible for driving data platform strategy, data operations, automation, infrastructure improvements, and governance while ensuring the organization has the technical capability to independently maintain and evolve its data environment.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or an equivalent combination of education and experience.
5+ years of experience designing, developing, and supporting enterprise data platforms, data warehouses, and large-scale data integration solutions.
3+ years of hands-on experience developing and supporting Snowflake data warehouse environments and dbt transformation frameworks.
Proficiency in SQL and Python, with experience developing data pipelines, automation solutions, and data engineering applications.
Strong understanding of data modeling, enterprise data architecture, ELT best practices, data quality, governance, and platform performance optimization.
Experience with cloud-based data platforms and infrastructure, including familiarity with AWS services such as S3, ECS, Lambda, and related cloud technologies.
Experience working within structured change management, release management, and IT governance processes.
Work authorization for the United States required.
Strong analytical, troubleshooting, communication, documentation, and problem-solving skills with the ability to independently make technical decisions and collaborate effectively across business and technical teams.

Nice To Haves

Experience with automation tooling such as Terraform, as well as source control and CI/CD practices preferred.
Experience with workflow orchestration tools such as Airflow, Dagster, or similar platforms preferred.
Experience working within a healthcare, MSO, IPA, Medical Group, Health Plan, or other HIPAA-regulated environment preferred.

Responsibilities

Serve as the technical owner of the organization's enterprise data platform, including Snowflake, dbt, and supporting data engineering technologies, ensuring the integrity, quality, availability, performance, and operational excellence of enterprise data assets.
Lead the design, development, governance, and ongoing optimization of dbt models, transformation logic, data pipelines, and enterprise data architecture to deliver trusted, reusable datasets for reporting, analytics, and operational decision-making.
Design, develop, and optimize scalable ELT pipelines using SQL and Python to integrate data from SQL Server, vendor applications, APIs, flat files, and other enterprise data sources into the Snowflake data warehouse.
Maintain and evolve the data platform by evaluating, implementing, and supporting infrastructure, automation, deployment processes, and operational tooling required to improve scalability, reliability, and maintainability.
Establish and maintain enterprise data quality standards, validation processes, monitoring, alerting, and documentation to ensure accurate, reliable, and trusted data across the organization.
Partner with business stakeholders, Business Intelligence developers, application owners, and internal IT teams to understand requirements, make data architecture decisions, and deliver scalable data solutions.
Collaborate with internal support teams and third-party vendors to troubleshoot complex data issues, support enterprise data integrations, and ensure reliable data movement across business systems.
Recommend improvements to data architecture, engineering standards, automation, infrastructure, and development practices while promoting data engineering best practices.
Ensure compliance with HIPAA, organizational security standards, change management processes, and IT governance requirements while maintaining the confidentiality and integrity of protected health information (PHI).