Lead Data & Analytics Engineer

In April 2025, Kandu Health and Neurolutions merged to form Kandu Inc. to pioneer an integrated approach to stroke recovery, combining FDA-cleared brain‑computer interface technology with personalized telehealth services. The company’s Ipsi Hand® device is durable medical equipment that enables chronic stroke survivors to regain upper extremity function in daily home use. Combining this advanced technology with the support of expert clinicians offers a comprehensive path to recovery– helping survivors improve mobility, independence, and quality of life.

Kandu extends recovery beyond the hospital through principal illness navigation, providing one‑on‑one education, care coordination, and advocacy; grounded in clinical evidence and informed by the lived experiences of patients and their families.

The Lead Data & Analytics Engineer will be a foundational member of Kandu’s Enterprise Systems & Intelligence (ESI) team, a new function responsible for building Kandu’s unified digital operating system and enabling data‑driven, intelligent workflows across the enterprise.

You will help architect and build the data infrastructure that connects our core business systems, turning disparate operational data into clean, governed, insight‑ready assets. You will design pipelines, model and transform data, build the enterprise data warehouse, deliver dashboards, and contribute to early predictive modeling. Your work will enable clinicians, commercial teams, market access, revenue cycle, operations, and leadership to make faster, more informed decisions.

This role is ideal for someone who loves building systems from scratch, thrives in ambiguity, and wants to be part of transforming a company into an insight‑driven, AI‑enabled enterprise.

• Build and maintain data pipelines from key business systems, including EHR, CRM, ERP, claims/finance, and manufacturing/ops
• Design ELT workflows to ingest, normalize, and transform data using modern tooling (e.g., Fivetran/Airbyte, Prefect/Airflow, dbt, Python)
• Ensure reliability, observability, version control, and documentation of all pipelines
• Handle PHI responsibly and ensure all pipelines, transformations, and data storage follow HIPAA, GDPR, and SOC2 requirements

• Architect, build, and implement a centralized data warehouse (e.g., in Snowflake, Big Query, or Redshift), including schemas, fact/dimension models, and semantic layers that reflect real‑world workflows
• Develop and maintain clean data models (dimensional, star/snowflake schemas), ensuring consistency across patient, clinical, sales, and claims datasets, to support analytics, dashboards, reporting and predictive models
• Ensure data quality, lineage, governance and consistency across domains

• Develop dashboards, operational monitors, and recurring analytics that provide real‑time visibility into clinical, commercial, market access, revenue cycle, finance, and manufacturing activities
• Automate recurring reporting workflows, alerts, and ETL orchestration (scheduling, monitoring, error handling)
• Enable self‑service analytics by ensuring data models are consistent, intuitive, and well‑documented
• Translate problems uncovered during discovery into actionable, well‑structured analytics and visualizations
• Support rapid ad hoc analysis during the early discovery phase of ESI

• Develop early predictive and prescriptive models, e.g. prior‑auth approval likelihood, therapy adherence patterns, claims‑denial risk, operational forecasting
• Support feature engineering, EDA and model evaluation under the direction of the VP of ESI
• Help lay the foundation for future AI‑driven decision support systems and embedding intelligence into operational systems

• Work closely with business stakeholders to understand requirements, pain points and data needs
• Communicate clearly with non‑technical teams and translate technical concepts into business language
• Support the ESI team’s mission to strengthen data‑driven decision‑making across…