The Role

We are hiring a Senior Data Engineer to join our team within the Data Architecture & Engineering practice. You will design, build, and maintain data pipelines that power healthcare payer analytics - including claims processing, contract configuration, pricing edits, and fee schedule ingestion. This is hands-on engineering work in a Snowflake and AWS environment, not a management role.

Work You ll Do

Design, develop, and maintain scalable data pipelines in Snowflake for healthcare claims, contract configuration, and fee-for-service reimbursement logic
Build and optimize ELT processes using Snowflake SQL, stored procedures, and dynamic SQL for complex healthcare datasets
Develop and maintain Apache Airflow DAGs (AWS MWAA) for pipeline orchestration, scheduling, and monitoring across multiple data domains
Write clean, testable Python scripts for data transformation, validation, web scraping automation, and API integrations
Implement and maintain CI/CD workflows using Bitbucket Pipelines and Liquibase for database migration and schema change management
Support data quality and governance processes, including Snowflake role-based access control, dynamic data masking, and schema patterns
Monitor pipeline health, troubleshoot failures, and resolve incidents across Snowflake, AWS Lambda, S3, SNS, and CloudWatch
Leverage AI coding assistants to accelerate development, with a focus on review, refinement, and quality assurance of AI-generated output
Collaborate with business analysts and project teams to translate healthcare business requirements into technical pipeline specifications
Document technical processes, pipeline architecture, and operational runbooks in Confluence
Other duties as assigned

Requirements

5+ years of hands-on data engineering experience
Proficiency in Snowflake: ELT pipeline development, stored procedures, query optimization, data modeling (star, snowflake, and hybrid schemas)
Strong SQL skills, including complex joins, window functions, CTEs, and dynamic SQL generation
Solid Python experience in a data engineering context (Pandas, file processing, API clients, web scraping with BeautifulSoup or Scrapy)
Experience with Apache Airflow for pipeline orchestration (AWS Managed Workflows for Apache Airflow preferred)
Hands-on experience with AWS services: S3, Lambda, SNS, CloudWatch, IAM
Proficiency with Git-based version control and CI/CD pipelines (Bitbucket Pipelines preferred)
Experience with database migration tooling (Liquibase preferred)
Demonstrated ability to work independently and manage priorities across concurrent workstreams
Strong written and verbal communication skills in English, with the ability to collaborate effectively across time zones
Experience working in globally distributed teams

Preferred Qualifications

Healthcare payer domain experience: claims data, provider contracts, fee schedules, or pricing analytics
Experience with data governance frameworks, HIPAA compliance, and PHI handling in cloud environments
Familiarity with Power BI for data visualization and reporting
Experience with AI-assisted development tools (Claude Code, GitHub Copilot, or similar)
Familiarity with Terraform or infrastructure-as-code practices
Unit testing and test-driven development practices for data pipelines
Agile delivery experience (Scrum or Kanban), including sprint planning and backlog management in Jira
Bachelor s degree in Computer Science, Engineering, or a related field (or equivalent practical experience)

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Senior Data Engineer

Job Description

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