Senior Analytics Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with clinical, operational, and business teams to gain a comprehensive understanding of business processes and workflows, translating requirements into scalable data models, curated datasets, standardized metrics, and AI-ready data assets that facilitate analytics, machine learning, and informed decision-making.

• Streamline and operationalize intricate data and AI requirements by breaking down problems, identifying crucial assumptions, and designing maintainable, production-level data and feature pipelines.

• Create, build, and enhance data transformation pipelines and analytics models utilizing cloud platforms (e.g., Azure Data Factory, Databricks, Microsoft Fabric).

• Develop and sustain feature engineering pipelines to support machine learning applications (e.g., risk scoring, readmission prediction, utilization forecasting).

• Construct reusable data marts and feature stores that cater to both BI and AI/ML workloads.

• Collaborate with data scientists and ML engineers to prepare high-quality, model-ready datasets and ensure consistency between training and inference data.

• Assist in integrating AI/ML outputs into clinical and operational workflows (e.g., alerts, prioritization queues, decision support tools).

• Develop and refine semantic models, curated datasets, and dashboards in Databricks/Power BI/Tableau, ensuring alignment with standardized metrics and ML-derived insights.

• Engage directly with healthcare datasets, including claims, clinical, and operational data, ensuring accurate interpretation for both analytics and ML applications.

• Ingest, transform, and normalize healthcare data using standards like ICD-10, CPT, NDC, ensuring interoperability and consistency.

⛳️ Requirements

• Bachelor’s degree in information technology, Computer Science, or a related field, or equivalent experience.

• Over 5 years of experience working with healthcare data in analytics engineering, data engineering, or related data-focused roles, with increasing responsibility for data modeling and analytics solutions.

• Extensive experience with claims and clinical datasets in payer and/or provider environments, with the capability to convert data into actionable insights.

• Previous experience in designing and constructing scalable data models, curated data marts, and semantic layers to support BI and analytics applications.

• Profound understanding of healthcare data standards and vocabularies (e.g., ICD-10, CPT, SNOMED) and their application in analytics and interoperability scenarios.

• Familiarity with cloud data platforms (Azure preferred; AWS or GCP acceptable), including modern data stack components like data lakes/lakehouses, distributed processing (e.g., Databricks/Spark), and orchestration tools.

• Strong SQL proficiency and experience with at least one programming language such as Python or Scala, focusing on data transformation, validation, and performance optimization.

• Experience in feature engineering and preparing ML-ready datasets, including assembling training datasets and supporting data pipelines for predictive applications.

• Proven ability to transition from ambiguity to clarity by converting business challenges into structured data solutions, emphasizing scalability over one-time builds.

• Background in a healthcare services, payer, or provider organization.

• Excellent communication skills with the ability to convey 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 is 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.