Senior Analytics Engineer Jobs

About The Position

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• At least 5 years of experience building cloud-native data and machine-learning engineering solutions.
• At least 5 years of programming experience in Python (PySpark) and SQL.
• At least 3 years of experience deploying data and feature pipelines, model training, and inferencing within the Databricks stack.
• At least 3 years of hands-on experience with Databricks, PostgreSQL, and distributed data processing frameworks such as Apache Spark.
• At least 3 years of hands-on experience with the Databricks ML stack, including MLflow, Databricks Notebook, and Runtime ML.
• Ability to communicate technical concepts clearly to non-technical business and clinical stakeholders and rapidly translate ambiguous, in-the-field requirements into working solutions.
• For home-based work, self-provided internet service must provide at least 25 Mbps download and 10 Mbps upload speed.
• For home-based work, maintain a dedicated workspace without ongoing interruptions to protect member PHI/HIPAA information.

Nice To Haves

• Experience in the healthcare or insurance industry; payer experience is strongly preferred.
• Familiarity with healthcare standards such as FHIR and HL7.
• Prior customer-facing, consulting, solutions engineering, or forward-deployed engineering experience, including gathering requirements, running demonstrations, and delivering solutions on tight timelines.
• Experience with Delta Lake or Lakehouse architecture.
• Experience with orchestration tools such as Airflow or Azure Data Factory.
• Experience with streaming technologies such as Kafka or Event Hubs.
• Knowledge of DevOps and CI/CD pipelines, such as Azure DevOps or GitHub Actions.

Responsibilities

• Develop scalable and cost-efficient data and machine-learning solutions using Databricks, Spark, and cloud-native services.
• Build and optimize ETL/ELT workflows for structured and unstructured healthcare data, including claims, clinical, provider, and consumer data.
• Develop and maintain data models in enterprise data warehouses and support Lakehouse architecture using Databricks, Delta Lake, and cloud storage.
• Build batch and real-time data 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.
• Use Databricks Genie to enable natural-language querying and broader data access for business stakeholders.
• Design and optimize semantic layers and governed datasets for trusted Genie-driven insights.
• Collaborate with stakeholders to turn business questions into AI-assisted analytics workflows and ensure AI outputs are accurate, explainable, and compliant.
• Lead enterprise-scale design and architecture discussions and establish data and ML engineering, testing, and CI/CD best practices.
• Work directly with assigned business and analytics teams to understand capabilities, workflows, pain points, and success criteria.
• Lead requirements discovery, workshops, and working sessions; translate evolving business needs into technical specifications and delivery plans.
• Rapidly prototype, configure, and demonstrate solutions to validate direction and reduce risk.
• Advise business and clinical stakeholders while balancing engineering rigor with pragmatic delivery.
• Train end users, gather usage feedback, and iterate on solutions to drive adoption.
• Partner with product, UX, and business subject-matter experts to identify and deliver solutions.
• Ingest, normalize, and optimize healthcare producer/agent, broker, commission, and distribution data 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 readiness for regulatory reporting.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 401(k) retirement savings plan
• Paid time off
• Company holidays
• Personal holidays
• Paid parental leave
• Paid caregiver leave
• Short-term disability
• Long-term disability
• Life insurance
• Bonus incentive plan