GCP Data Engineer

About the role

As a GCP Data Engineer, you will modernize healthcare data quality and campaign processing platforms through cloud-based engineering solutions on Google Cloud Platform (GCP). You will collaborate with architects, business stakeholders, healthcare operations teams, and cross-functional technology partners to design, build, and optimize scalable data solutions.

Responsibilities

• Lead the migration of healthcare Data Quality (DQI) campaign pipelines from legacy platforms to Google Cloud Platform.
• Develop and enhance Python-based solutions, converting SAS macros into scalable, reusable modules supporting drug targeting, member eligibility, claims processing, formulary logic, and vendor file generation.
• Design, build, and maintain Apache Airflow workflows in Google Cloud Composer to orchestrate complex healthcare campaign processes with parallel execution and automated scheduling.
• Create and manage BigQuery datasets, tables, and views to support campaign orchestration, state tracking, reporting, and operational analytics.
• Implement scalable cloud architecture patterns, including ephemeral cluster deployment strategies and concurrent processing models to improve performance and efficiency.
• Develop automated validation and quality assurance frameworks to ensure data accuracy and consistency between legacy and modernized platforms.
• Partner with business and technical teams to troubleshoot data issues, optimize workflows, and support production operations.

Requirements

• Strong experience in data engineering, data migration, or cloud modernization projects.
• Hands-on experience with Google Cloud Platform (GCP), including BigQuery, Cloud Storage (GCS), and Google Cloud Composer.
• Advanced Python development experience, including building reusable frameworks, data processing applications, and automation solutions.
• Experience migrating legacy analytics or ETL platforms, such as SAS, to modern cloud-native technologies.
• Expertise developing and managing Apache Airflow DAGs, workflow orchestration, and production scheduling processes.
• Experience designing scalable data processing architectures utilizing parallel execution and performance optimization techniques.
• Strong understanding of healthcare data domains, including claims, member eligibility, pharmacy, or population health datasets.
• Experience implementing data quality validation, reconciliation, and testing frameworks.
• Strong SQL skills and experience designing data models, tables, and views.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent professional experience.

Preferred Qualifications

• Experience with healthcare campaign management or customer outreach platforms.
• Knowledge of Vertex AI and machine learning enablement within GCP.
• Experience with YAML-based configuration frameworks and metadata-driven application design.
• Familiarity with EDM workflows and enterprise file transfer automation.
• Experience working within highly regulated healthcare or payer environments.
• Knowledge of cloud infrastructure optimization, distributed processing, and workload scalability.
• Experience supporting enterprise-scale data modernization and digital transformation initiatives.

Schedule

This is a hybrid position requiring 3 days a week in a client or Cognizant office in Hartford, CT.

Pay

The annual salary for this position is between $85,000 - $100,000 depending on experience and other qualifications. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan