GCP Data Engineer - Remote
Computing Concepts, Inc.
New York City, NY(remote)
Summary: Strong experience architecting enterprise data platforms on Google Cloud (GCP). The architect will work as a strategic technical partner to design and build a GCP BigQuery-based Data Lake & Data Warehouse ecosystem.
The role requires deep hands-on expertise in data ingestion, transformation, modeling, enrichment, and governance, combined with a strong understanding of clinical healthcare data standards, interoperability, and cloud architecture best practices.
Key Responsibilities:
- Data Lake & Data Platform Architecture (GCP)
* Architect and design an enterprise-grade GCP-based data lakehouse leveraging BigQuery, GCS, Dataproc, Dataflow, Pub/Sub, Cloud Composer, and BigQuery Omni.
* Define data ingestion, hydration, curation, processing and enrichment strategies for large-scale structured, semi-structured, and unstructured datasets.
* Create data domain models, canonical models, and consumption-ready datasets for analytics, AI/ML, and operational data products.
* Design federated data layers and self-service data products for downstream consumers.
- Data Ingestion & Pipelines
* Architect batch, near-real-time, and streaming ingestion pipelines using GCP Cloud Dataflow, Pub/Sub, and Dataproc.
* Set up data ingestion for clinical (EHR/EMR, LIS, RIS/PACS) datasets including HL7, FHIR, CCD, DICOM formats.
* Build ingestion pipelines for non-clinical systems (ERP, HR, payroll, supply chain, finance).
* Architect ingestion from medical devices, IoT, remote patient monitoring, and wearables leveraging IoMT patterns.
* Manage on-prem → cloud migration pipelines, hybrid cloud data movement, VPN/Interconnect connectivity, and data transfer strategies.
- Data Transformation, Hydration & Enrichment
* Build transformation frameworks using BigQuery SQL, Dataflow, Dataproc, or dbt.
* Define curation patterns including bronze/silver/gold layers, canonical healthcare entities, and data marts.
* Implement data enrichment using external social determinants, device signals, clinical event logs, or operational datasets.
* Enable metadata-driven pipelines for scalable transformations.
- Data Governance & Quality
* Establish and operationalize a data governance framework encompassing data stewardship, ownership, classification, and lifecycle policies.
* Implement data lineage, data cataloging, and metadata management using tools such as Dataplex, Data Catalog, Collibra, or Informatica.
* Set up data quality frameworks for validation, profiling, anomaly detection, and SLA monitoring.
* Ensure HIPAA compliance, PHI protection, IAM/RBAC, VPC SC, DLP, encryption, retention, and auditing.
- Cloud Infrastructure & Networking
* Work with cloud infrastructure teams to architect VPC networks, subnetting, ingress/egress, firewall policies, VPN/IPSec, Interconnect, and hybrid connectivity.
* Define storage layers, partitioning/clustering design, cost optimization, performance tuning, and capacity planning for BigQuery.
* Understand containerized processing (Cloud Run, GKE) for data services.
- Stakeholder Collaboration
* Work closely with clinical, operational, research, and IT stakeholders to define data use cases, schema, and consumption models.
* Partner with enterprise architects, security teams, and platform engineering teams on cross-functional initiatives.
* Guide data engineers and provide architectural oversight on pipeline implementation.
- Hands-on Leadership
* Be actively hands-on in building pipelines, writing transformations, building POCs, and validating architectural patterns.
* Mentor data engineers on best practices, coding standards, and cloud-native development.
Required Skills & Qualifications
Technical Skills (Must-Have)
* 10+ years in data architecture, engineering, or data platform roles.
* Strong expertise in GCP data stack (BigQuery, Dataflow, Composer, GCS, Pub/Sub, Dataproc, Dataplex).
* Hands-on experience with data ingestion, pipeline orchestration, and transformations.
* Deep understanding of clinical data standards:
* HL7 v2.x, FHIR, CCD/C-CDA
* DICOM (for scans and imaging)
* LIS/RIS/PACS data structures
* Experience with device and IoT data ingestion (wearables, remote patient monitoring, clinical devices).
* Experience with ERP datasets (Workday, Oracle, Lawson, PeopleSoft).
* Strong SQL and data modeling skills (3NF, star/snowflake, canonical and logical models).
* Experience with metadata management, lineage, and governance frameworks.
* Solid understanding of HIPAA, PHI/PII handling, DLP, IAM, VPC security.
Cloud & Infrastructure
* Solid understanding of cloud networking, hybrid connectivity, VPC design, firewalling, DNS, service accounts, IAM, and security models.
* Cloud Native Data movement services
* Experience with on-prem to cloud migrations.