Senior Forward Deployed Engineer – Data & Analytics

This is a fully remote position, open to applicants in Florida, +9 more locations.

📋 Description

• Design and implement scalable, cost-effective Data & ML solutions utilizing Databricks (Spark) and cloud-native services.

• Create and enhance ETL/ELT workflows for both structured and unstructured healthcare data.

• Develop and manage data models within enterprise data warehouses.

• Support Lakehouse architecture by utilizing Databricks, Delta Lake, and cloud storage solutions.

• Construct real-time and batch processing pipelines for analytics and operational applications.

• Execute data transformations using PySpark and SQL in the Databricks environment.

• Integrate data from APIs, third-party providers, and internal systems.

• Utilize Databricks Genie to facilitate natural-language querying and broaden data accessibility.

• Design and enhance semantic layers and governed datasets to yield Genie-driven insights.

• Collaborate with stakeholders to convert business inquiries into AI-supported analytics workflows.

• Ensure that AI-generated outputs are accurate, understandable, and compliant with healthcare data governance and HIPAA standards.

• Lead discussions on enterprise-scale data and ML architecture.

• Establish optimal practices in data and ML engineering, testing, and CI/CD processes.

• Function as an embedded, customer-facing engineer for designated business or analytical teams.

• Facilitate requirements gathering, working sessions, and discovery workshops.

• Prototype, configure, and demonstrate solutions to stakeholders.

• Provide guidance to business and clinical stakeholders on technical solutions.

• Promote post-launch adoption through end-user training, feedback collection, and iterative improvements.

• Collaborate with product, UX, and business subject-matter experts to expedite solution delivery.

• Ingest, normalize, and optimize healthcare datasets, including producer/agent, broker, commission, and distribution data.

• Implement data security measures, including encryption, masking, and access control protocols.

• Maintain data lineage, audit trails, and readiness for regulatory reporting.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.

• Over 5 years of experience in building cloud-native Data & ML engineering solutions.

• More than 5 years of programming expertise in Python (PySpark) and SQL.

• At least 3 years of experience in deploying data and feature pipelines, model training, and inferencing within the Databricks framework.

• A minimum of 3 years of practical experience with Databricks.

• At least 3 years of hands-on experience with PostgreSQL.

• A minimum of 3 years of experience with distributed data processing frameworks, including Apache Spark.

• At least 3 years of hands-on experience with the Databricks ML stack, including MLflow, Databricks Notebook, and Runtime ML.

• Capability to clearly communicate technical concepts to non-technical business and clinical stakeholders.

• Ability to transform ambiguous, real-world requirements into functional solutions.

• Minimum home internet speed of 25 Mbps download and 10 Mbps upload for remote or hybrid home/office employees.

• A dedicated workspace free from ongoing interruptions to safeguard member PHI/HIPAA information.

🏝️ Benefits

• Bonus incentive plan based on individual and/or company performance.

• Medical, dental, and vision insurance benefits.

• 401(k) retirement savings plan.

• Paid time off.

• Company and personal holidays.

• Paid parental and caregiver leave.

• Short-term and long-term disability coverage.

• Life insurance benefits.

• Requirement for a dedicated workspace to protect member PHI/HIPAA information.

• Remote work arrangement with occasional travel to Humana offices for training or meetings.