Lead Data & Analytics Engineer

Kandu, Inc. is pioneering an integrated approach to stroke recovery by combining FDA-cleared brain-computer interface technology with personalized telehealth services. The Lead Data & Analytics Engineer will be responsible for building Kandu’s unified digital operating system, architecting data infrastructure, and enabling data-driven workflows across the enterprise.

Responsibilities:

• 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, BigQuery, 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 the company

Requirements:

• 5–8 years of experience in data engineering, analytics engineering, or a full-stack data role spanning pipelines, modeling, and dashboards
• Strong SQL and Python skills (must be confident building production-grade pipelines)
• Experience with modern data stack tools (Airflow/Prefect, dbt, Fivetran/Airbyte, Snowflake/BigQuery/Redshift)
• Experience designing star schemas, dimensional models, or semantic layers
• Strong dashboarding experience (Looker, Tableau, PowerBI, Mode, Sigma, etc.)
• Ability to work across messy, unstructured and inconsistent SaaS data sources
• Comfort integrating data from multiple SaaS systems via APIs, webhooks, and vendor interfaces
• Excellent communication skills and comfort partnering with cross-functional teams
• Ability to thrive in ambiguity and build v1 systems with limited infrastructure
• Employment eligibility to work in the United States is required. The company does not sponsor employment visas for this position at this time
• Experience in healthcare (EHR data, claims, RCM, prior auth, ERP, medical device workflows)
• Familiarity with HIPAA/security considerations for pipelines and stored data
• Experience contributing to early-stage predictive modeling (sklearn, XGBoost, time series)
• Experience improving operational workflows or enabling digital transformation
• Knowledge of Salesforce data model, clinical systems, and ERP/RCM systems is a plus