Principal Data Engineer

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

Originally posted on Himalayas