Senior Forward Deployed Engineer

Humana is seeking a Senior Forward Deployed Engineer to support its mission of improving the health and well-being of its consumers.

This role will focus on building scalable, secure, data & analytics solutions that power analytics, clinical insights, and business decision-making across the enterprise.

As a Forward Deployed Engineer, this individual will work directly alongside business and analytics stakeholders, translating real-world problems into working solutions quickly and driving adoption across the enterprise.

The ideal candidate will have strong experience with cloud-based data platforms, Databricks, PostgreSQL, and healthcare data, with a passion for delivering high-quality, trusted data solutions in a regulated environment.

Key Responsibilities

Data & ML Engineering

• Develop scalable and cost-efficient Data & ML solutions using Databricks (Spark) and cloud-native services
• Build and optimize ETL/ELT workflows for ingesting structured and unstructured healthcare data (claims, clinical, provider, and consumer data)
• Develop and maintain data models in enterprise data warehouses
• Support Lakehouse architecture leveraging Databricks, Delta Lake, and cloud storage

Advanced Data Processing

• Build real-time and batch pipelines for analytics and operational use cases
• Develop data transformations using PySpark and SQL within Databricks
• Integrate data from APIs, third-party vendors, and internal systems

AI & Advanced Analytics (Databricks Genie)

• Leverage Databricks Genie (AI/BI capabilities) to enable natural language querying and democratize data access for business stakeholders
• Design and optimize semantic layers and governed datasets that power Genie-driven insights with trusted, high-quality data
• Collaborate with stakeholders to translate business questions into AI-assisted analytics workflows using Databricks
• Ensure AI outputs are accurate, explainable, and compliant with healthcare data governance and HIPAA requirements

Technical Leadership

• Lead design and architecture discussions for enterprise scale solutions
• Establish and enforce best practices in data & ML engineering, testing, and CI/CD

Collaboration & Customer-Facing Delivery

• Serve as the embedded, customer-facing engineer for assigned business or analytical teams, working directly with end users, to understand existing capabilities & workflows, pain points, and success criteria
• Lead requirements discovery end-to-end: run working sessions and discovery workshops, translate ambiguous, evolving business problems into concrete technical specifications and delivery plans
• Rapidly prototype, configure, and demo solutions to stakeholders to validate direction early and de-risk larger investments
• Act as a trusted technical advisor to business and clinical stakeholders, balancing engineering rigor with pragmatic, fast-turnaround delivery to accelerate time-to-value and drive adoption of new tools and datasets
• Drive post-launch adoption by training end users, gathering hands-on usage feedback, and iterating quickly on delivered solutions in response to that feedback
• Blend engineering, product discovery, and solution delivery skills, partnering with product, UX, and business SMEs to identify and ship solutions rapidly

Healthcare Data & Compliance

• Work with healthcare datasets, including producer/agent, broker, commission, and distribution data, ensuring proper ingestion, normalization, and optimization for analytics and reporting
• Ensure compliance with HIPAA, HITECH, and enterprise data governance policies
• Implement data security, encryption, masking, and access controls
• Maintain data lineage, auditability, and regulatory reporting readiness

Required Qualifications

• Bachelor's in Computer Science, Engineering, or related field
• 5+ years of experience in building cloud-native Data & ML engineering solutions
• 5+ years of programming experience in Python (PySpark) and SQL
• 3+ years of experience in deploying data & feature pipelines, model training, and inferencing within the Databricks stack
• 3+ years of hands-on experience with:
• Databricks
• PostgreSQL
• Distributed data processing frameworks (Apache Spark)
• Databricks ML stack including MLflow, Databricks Notebook, Runtime ML, etc.
• Demonstrated ability to communicate technical concepts clearly to non-technical business and clinical stakeholders, and to rapidly translate ambiguous, in-the-field requirements into a working solution

Preferred Qualifications

• Experience in healthcare or insurance industry (payer experience strongly preferred)
• Familiarity with healthcare standards (e.g., FHIR, HL7)
• Prior experience in a customer-facing, consulting, solutions engineering, or forward-deployed engineering role, engaging directly with end users to gather requirements, run demos, and deliver solutions on tight timelines
• Experience with:
• Delta Lake / Lakehouse architecture
• Orchestration tools (Airflow, Azure Data Factory)
• Streaming (Kafka, Event Hubs)
• Knowledge of DevOps and CI/CD pipelines (Azure DevOps, GitHub Actions)

Benefits

• Medical, dental, and vision benefits
• 401(k) retirement savings plan
• Time off (including paid time off, company and personal holidays, paid parental and caregiver leave)
• Short-term and long-term disability
• Life insurance