Data Engineer - GCP

• Job Description

We are seeking a GCP Data Engineer to design, build, and maintain our enterprise data platform, with a primary focus on BigQuery development and optimization. You will be responsible for developing robust ETL pipelines to migrate and load data from our on-premises systems to GCP, ensuring data quality and reliability at scale. In this role, you will support our existing data infrastructure, troubleshoot production issues, and collaborate with analytics and business teams to enable data-driven decision-making. Ensures systems compliance to applicable laws, regulatory standards and policies.

Job Responsibility

• Design, build, and maintain scalable and reliable ELT/ETL pipelines to ingest data from a wide variety of sources (APIs, databases, event streams, flat files).
• Orchestrate, schedule, and monitor data workflows using tools like Cloud Composer (Airflow), ensuring high data availability and quality.
• Collaborate with analysts, data scientists, and product managers to understand data requirements and deliver high-impact data solutions.
• Implement and manage data infrastructure using Infrastructure as Code (IaC) principles (e.g., Terraform).
• Analyze query performance, diagnose execution plan bottlenecks, and refactor complex SQL to improve speed and efficiency.
• Monitor Google BigQuery slot utilization, identify resource-intensive jobs, and make data-driven recommendations on optimization opportunities
• Develop and enforce a robust data security framework using IAM roles, Row-Level Security, and Column-Level Security to ensure data is secure and compliant with the principle of least privilege
• Implement data masking policies to protect personally identifiable information (PII) and other sensitive data
• Utilize Cloud Logging and audit logs to monitor data access, support compliance requirements (GDPR, CCPA, etc.), and investigate security events
• Implements the information system initiatives to meet user requirements; communicates with user departments and project teams regarding implementation activities and system changes to ensure feasibility; develops system specifications that appropriately meet department requirements. 
• Assesses the patient management inpatient and outpatient registration pathways for constant improvement and enhancement; incorporates financial regulatory requirements; administers system support for patient management system users; evaluates information technology to promote operational efficiency and financial reimbursement. 
• Reviews contractual obligations, ensures status of deliverables, and resolves related issues; performs periodic post-installation reviews of system initiatives. 
• Reviews and evaluates post-installation processing per documented specifications; creates ad-hoc reports to ensure system builds are functioning according to specifications and ensures accurate payments. 
• Develops and conducts in-services for Patient Financial Services/Accounts; creates appropriate in-service training materials. 
• Conducts system-wide in-services with managers and staff, as necessary; ensures systems compliance to applicable laws, regulatory standards and policies. 
• Operates under general guidance and work assignments are varied and require interpretation and independent decisions on course of action. 
• Performs related duties as required. All responsibilities noted here are considered essential functions of the job under the Americans with Disabilities Act. Duties not mentioned here, but considered related are not essential functions.

Job Qualification

• Bachelor's Degree required, or equivalent combination of education and related experience   
• Minimum of two (2) years of experience  with Apache Hadoop, NoSQL, setting up cloud clusters, Apache Spark, and other advanced data science and big data technologies, required.
• Experience in software development in enterprise/ web/ cloud applications, solutioning, architecture and frameworks.
• Big data expertise with cloud and enterprise level design/implementation.
• Experience in architecting data warehouses and/or data lakes with traditional database enterprise-class RDBMS technologies.
• Strong knowledge of programming languages/tools including: Java, Python, Spark, SQL, R, and Shell Scripts.

HIGHLY PREFERRED

• Deep, hands-on expertise with Google BigQuery is a must.
• Expert-level SQL skills, including experience with query plan analysis and optimization.
• Strong experience building and managing ELT/ETL pipelines using modern data stack tools (e.g., dbt, Airflow