The Principal Data Engineer will lead the design of data architectures and analytics applications, collaborating with teams to build scalable platforms and improve data quality, while mentoring engineers and driving engineering best practices.
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.
Essential Job Duties
- 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 Job Dutes
- Other duties as assigned by supervisor or HHAeXchange leader.
Travel Requirements
- Travel up to 10%, including overnight travel
Required Education, Experience, Certifications and Skills
- 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
The base salary range for this US-based, full-time, and exempt position is $155,000-184,000/yr, not including variable compensation. An employee’s exact starting salary will be based on various factors including but not limited to experience, education, training, merit, location, and the ability to exemplify the HHAeXchange core values.
This is a benefits-eligible position. HHAeXchange offers competitive health plans, paid time-off, company paid holidays, 401K retirement program with a Company elected match, including other company sponsored programs.
HHAeXchange is an equal-opportunity employer. The Company offers employment opportunities to all applicants and employees without regard to race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, medical condition, marital status, veteran status, citizenship, genetic information, hairstyles, or any other status protected by local or federal law.
Similar Jobs
Cloud • Information Technology • Security • Software • Cybersecurity
Partner with sales to design and present data security solutions, lead technical evaluations and custom configurations, gather customer requirements, and drive successful hands-on proof-of-concept and evaluation outcomes for the Data Security business line.
Top Skills:
Data ProtectionSaas TechnologiesWeb TechnologiesZero Trust ExchangeZscaler
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.
Top Skills:
AirflowAWSBigQueryDaskDockerFlinkGCPKafkaKubeflowKubernetesLangchainLlamaindexMlflowMlops ToolsOciPulsarPythonSagemakerSnowflakeSparkVertex Ai
Artificial Intelligence • Fintech • Healthtech • Software
Lead the design and execution of a new enterprise data platform, ensuring metrics reliability and supporting AI-driven products, while mentoring engineers and collaborating across teams.
Top Skills:
AirflowCdcDbtFivetranKafkaLiquibaseOpenmetadataPythonSnowflakeSQLStreaming/Event Driven Architectures
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
