GCP Data & Integration Architect (US Citizen's only)
Job Description
GCP Data & Integration Architect – Provider Data Management
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Location: Philadelphia, PA / Princeton, NJ Area
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Remote with occasional onsite visits
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Duration: 6+ Months Contract
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Role Overview
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We are seeking a highly skilled, hands-on GCP Data & Integration Architect to lead the design and implementation of a scalable, real-time data integration ecosystem supporting enterprise Provider
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Data Management.
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The ideal candidate will combine deep data engineering expertise with architectural leadership and have a proven track record of designing high-performance, cloud-native data platforms. This role will be responsible for establishing trusted, governed data products and scalable integration capabilities within a modern, cloud-first architecture.
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Key Responsibilities
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- Design and implement end-to-end data architectures using GCP services, including BigQuery, Dataflow, Pub/Sub, Dataproc, and Google Cloud Storage (GCS)
- Build scalable ingestion frameworks supporting batch, CDC, streaming, and event-driven integrations
- Architect real-time data pipelines using Kafka and cloud-native streaming technologies
- Design reusable and governed data products with clear consumption patterns
- Develop Master Data Management (MDM) and canonical data models to support a unified provider identity
- Architect and optimize distributed data processing pipelines using Apache Spark and Python
- Implement orchestration frameworks using Apache Airflow or equivalent technologies
- Design solutions for data quality, lineage, metadata management, and governance
- Support lakehouse architectures, including Bronze/Silver/Gold data layers
- Lead architecture across GCP and Azure environments with scalability and portability in mind
- Define cloud-native best practices for security, observability, performance, and cost optimization
- Implement Infrastructure as Code (Terraform) and CI/CD pipelines
- Support containerized deployments using Docker and Kubernetes
- Provide technical leadership, architecture guidance, design reviews, and hands-on support to engineering teams
- Establish reusable frameworks and scalable design patterns across data and integration platforms
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Required Qualifications
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- 10+ years of experience in data architecture, data engineering, or distributed systems
- Deep expertise in the Google Cloud Platform (GCP) data ecosystem, including:
- BigQuery
- Dataflow
- Pub/Sub
- Dataproc
- Google Cloud Storage (GCS)
- Strong hands-on experience with:
- Kafka and real-time streaming platforms
- Apache Spark – batch and streaming
- Python
- Apache Airflow or equivalent orchestration tools
- Proven experience designing and delivering:
- Real-time and event-driven integration architectures
- Large-scale, high-volume enterprise data platforms
- Strong understanding of:
- Data modeling and data warehousing
- Lakehouse architecture
- Metadata management
- Data governance and data quality frameworks
- Experience with:
- Microservices and event-driven architecture
- Docker and Kubernetes
- CI/CD and DevOps practices
- Infrastructure as Code, preferably Terraform
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Preferred Qualifications
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- Experience implementing enterprise MDM solutions or data product architectures
- Familiarity with data cataloging and governance platforms such as Atlan, Collibra, or Informatica
- Experience with healthcare or provider data is beneficial but not required
- Experience working in fast-paced, transformation-driven environments with evolving requirements
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What We’re Looking For
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- A hands-on architect who can both design and guide implementation
- Strong ability to influence senior stakeholders and cross-functional teams
- Ability to balance speed, scalability, performance, and governance
- Strong structured problem-solving skills and an iterative delivery mindset
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