Senior Data Engineer

Company - Our client is a nationally recognized healthcare marketing and medical education organization connecting patients and healthcare professionals at the point of care. The organization combines trusted educational content, data, and innovative technology to support more informed healthcare experiences nationwide.

Job Title - Senior Data Engineer

Location - Hybrid — 3 days per week onsite in Montvale, NJ

Role Type - 6–12 month contract

Must Have Skills:

• Strong BigQuery and Google Cloud Platform (GCP) expertise, including hands-on experience working in BigQuery
• Advanced SQL expertise, including writing and optimizing complex queries
• Strong ETL/ELT pipeline development and management experience, including building and operating scalable, reliable data pipelines
• Strong Python experience for data transformation, automation, and pipeline development
• API-based data integration experience, including incorporating API-sourced data into ETL/ELT workflows and handling pagination, rate limits, retries, schema drift, and partial failures

Responsibilities and Job Details:

• Own and enhance the data foundation supporting reporting, analytics, and business decision-making across the organization.
• Design, build, and maintain scalable data pipelines that move data from source systems through transformation into analytics-ready datasets.
• Develop and improve orchestration workflows to ensure reliable and timely data availability for reporting and downstream consumption.
• Build and support API-driven ingestion patterns across internal and external systems, accounting for real-world API behavior and failure scenarios.
• Develop and maintain data models, warehouse entity relationships, datasets, and views optimized for operational reporting and performance analytics.
• Implement data governance and quality practices, including validation, completeness testing, reconciliation, lineage, and documentation.
• Build monitoring and alerting capabilities around pipeline health, data freshness, failures, and SLA adherence.
• Optimize pipeline performance, BigQuery query efficiency, and warehouse cost management.
• Support reverse ETL and outbound workflows that deliver curated datasets back into operational systems through APIs.
• Integrate and model business-critical data from ERP and CRM platforms, including NetSuite and Salesforce.
• Collaborate cross-functionally with analytics, product, engineering, and business stakeholders to deliver trusted data solutions.
• Leverage modern development and AI/LLM tooling to accelerate data and analytics workflows, with exposure to platforms such as GitHub Copilot and Claude considered beneficial.