Senior Analytics Engineer

🔥 9 hours ago

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HarmonyCares

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1993

🏥 Healthcare

⚕️ Healthcare Insurance

💰 Venture Round on 2021-11

Healthcare • Healthcare Insurance • Home Health

HarmonyCares is a leading provider of comprehensive, home-based healthcare services across 15 states in the U. S. The company specializes in in-home physician care, skilled nursing, therapy, and hospice care for patients, particularly those with Medicare and complex medical conditions. HarmonyCares aims to offer dignified, patient-centered care, allowing individuals to maintain their health and independence in the comfort of their own homes.

📋 Description

• Collaborate across clinical, operational, and business teams to deeply understand business processes and workflows, translating needs into scalable data models, curated datasets, standardized metrics, and AI-ready data assets that support analytics, machine learning, and decision-making • Simplify and operationalize complex data and AI requirements by decomposing problems, identifying key assumptions, and designing maintainable, production-grade data and feature pipelines • Design, build, and optimize data transformation pipelines and analytics models using cloud platforms (e.g., Azure Data Factory, Databricks, Microsoft Fabric) • Develop and maintain feature engineering pipelines to support machine learning use cases (e.g., risk scoring, readmission prediction, utilization forecasting) • Build reusable data marts and feature stores that serve both BI and AI/ML workloads • Partner with data scientists and ML engineers to prepare high-quality, model-ready datasets and ensure consistency between training and inference data • Help embed AI/ML outputs into clinical and operational workflows (e.g., alerts, prioritization queues, decision support tools) • Develop and optimize semantic models, curated datasets, and dashboards in Databricks/Power BI/Tableau, ensuring alignment with standardized metrics and ML-derived insights • Work hands-on with healthcare datasets, including claims, clinical, and operational data, ensuring correct interpretation for both analytics and ML use cases • Ingest, transform, and normalize healthcare data using standards such as ICD-10, CPT, NDC, ensuring interoperability and consistency

🎯 Requirements

• Bachelor’s degree in information technology, Computer Science, or a related field, or equivalent experience • 5+ years of experience working with healthcare data in analytics engineering, data engineering, or related data-focused roles, with increasing ownership of data modeling and analytics solutions • Strong prior experience working with claims and clinical datasets across payer and/or provider environments, with the ability to translate data into actionable insights • Prior experience designing and building scalable data models, curated data marts, and semantic layers to support BI and analytics use cases • Deep understanding of healthcare data standards and vocabularies (e.g. ICD-10, CPT, SNOMED) and their application in analytics and interoperability use cases • Experience with cloud data platforms (Azure preferred; AWS or GCP acceptable), including modern data stack components such as data lakes/lakehouses, distributed processing (e.g., Databricks/Spark), and orchestration tools • Strong proficiency in SQL and experience with at least one programming language such as Python or Scala, with an emphasis on data transformation, validation, and performance optimization • Familiarity with feature engineering and preparing ML-ready datasets, including assembling training datasets and supporting data pipelines for predictive use cases • Demonstrated ability to move from ambiguity to clarity by translating business problems into structured data solutions, with a focus on scalability over one-off builds • Experience in a healthcare services, payer, or provider organization • Strong communication skills with the ability to translate complex technical concepts into business-friendly insights and influence both technical and non-technical stakeholders • Hands-on experience with Databricks (Spark, notebooks, Delta Lake, workflows) preferred • Knowledge of CI/CD, infrastructure-as-code, or data platform automation preferred

🏖️ Benefits

• Health, Dental, Vision, Disability & Life Insurance, and much more • 401K Retirement Plan (with company match) • Tuition, Professional License and Certification Reimbursement • Paid Time Off, Holidays and Volunteer Time • Paid Orientation and Training