Hhaexchange3mo ago

Principal Data Engineer

United StatesRemoteFull Timelead

Data EngineeringData EngineerDataData & AI

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HHAeXchange is the leading technology platform for home and community-based care. Founded in 2008, HHAeXchange was born out of an idea to create a fully comprehensive end-to-end homecare solution to help people who are aging or have disabilities thrive in their homes and communities. Our employees are passionate about transforming the healthcare space by building the only homecare ecosystem that fully connects patients, personal care providers, managed care organizations, and states.

The Principal Data Engineer will lead the design, development, and optimization of our data platforms and advanced analytics applications. This senior technical role will collaborate closely with engineering, product, operations, and customer success teams to define architectural direction, drive best practices, and guide cross-functional efforts to build scalable, reliable, and high-performance data platforms. This role will directly power advanced analytics, machine learning, and mission-critical business operations across the organization with significant impact on our customers and patients.

To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily with or without reasonable accommodation. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

This is a fully remote opportunity for candidates located in the EST or CST time zones within the US only.

Design end-to-end data architectures, frameworks, and pipelines that support large-scale and complex data ingestion, processing, transformations, reporting, and analytics.

Collaborate with stakeholders to ensure alignment with business and product strategies.

Build and optimize robust ETL/ELT workflows, data models, and distributed data processing jobs.

Implement best-in-class solutions using technologies such as Python, SQL, dbt, DMS, AWS Glue, Airflow, Docker/Kubernetes, Snowflake, and other cloud-native services.

Develop best practices to ensure data quality, integrity, lineage, governance, performance, and reliability across all pipelines, data platforms, and analytics applications.

Establish and maintain SLAs, monitoring, and alerting for mission-critical data services with observability design and implementation.

Identify and resolve performance bottlenecks to ensure scalable and cost-efficient data processing.

Provide technical leadership and mentorship to senior and junior engineers across the organization.

Promote engineering excellence and best practices in data engineering and developer experience —including CI/CD, infrastructure as code (IaC), automated testing, observability, security/privacy, and AI assistant tools.

Lead complex problem-solving initiatives and guide decisions on tools, technologies, and design patterns.

Partner with data engineers, software engineers, QA, product managers, customer success, and business leaders to define data requirements and deliver high-impact solutions.

Other duties as assigned by supervisor or HHAeXchange leader.

Travel up to 10%, including overnight travel

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field highly desirable.

8+ years of combined software and data engineering experience with a strong focus on distributed data processing and data-intensive applications.

5+ years of experience architecting, implementing, and maintaining reporting and analytics tools (e.g., Looker, Power BI, Tableau), with knowledge of data visualization best practices.

3+ years of experience working in highly regulated industries, with a preference for healthcare or homecare.

Proven expertise in Python, SQL, query and database optimization, data pipelines, data modeling, data governance, data catalog/data lineage management, and privacy/security best practices.

Deep experience with cloud platforms (AWS, Azure, or GCP) and modern data warehousing technologies (Snowflake, BigQuery, Redshift, etc.).

Demonstrated ability to lead large-scale data initiatives and influence architectural decisions across teams.

Excellent communication and collaboration skills, with the ability to translate complex technical concepts for diverse stakeholders.

Experience designing data platforms that support ML/AI workflows preferred.

Hands-on experience in AI/ML, LLMs, agentic development, and AI assistant tools preferred.

Experience in healthcare or homecare technology (EHR, HL7/FHIR) and product development preferred

Willingness to explore and adopt AI tools responsibly to enhance productivity and innovation in your role