Senior GCP Data Engineer

TITLE: Senior GCP Data Engineer LOCATION: EST time zone DURATION: 6-12-month contract with a probable extension NO C2C 3RD PARTY VENDORS!!! JOB DESCRIPTION: Responsibilities • Develop robust data ingestion, transformation, and integration workflows using Python, SQL, and modern data engineering frameworks. • Build and maintain batch and streaming data pipelines leveraging technologies such as Kafka (or similar pub/sub tools). • Work with Google Cloud Platform (GCP) services, including Cloud Storage, Dataflow, Pub/Sub, BigQuery, Cloud Spanner and Cloud Functions • Develop and manage data APIs and interfaces (REST and GraphQL) to enable high-performance data access across microservices. • Implement CI/CD automation for data pipelines using GitHub Actions, Argo CD, or equivalent tools. • Collaborate with Data Scientists and MLOps teams to integrate ML/NLP models into data pipelines and production workflows. • Build and operationalize NLP data pipelines for structured and unstructured data sources • Enable continuous learning and model‐retraining workflows using Vertex AI, Kubeflow, or similar GCP‐native tooling. • Implement frameworks for observability and data quality, ensuring ML predictions, confidence scores, and fallback events are logged into data lakes or monitoring systems. • Support distributed data systems and ensure reliability, performance, and scalability of data infrastructure. Required Qualifications • 5 years of experience building data pipelines or backend data workflows using Python, Java, or similar languages. • 2 years of experience designing REST/GraphQL data services or integrating data APIs. • 2 years of experience with cloud platforms (GCP preferred; AWS or Azure acceptable). • 2 years working with streaming platforms like Kafka or equivalent. • 2 years of experience with databases (Postgres or similar relational systems). • 2 years of experience with CI/CD tools (GitHub Actions, Jenkins, Argo CD, etc.). Preferred Qualifications • Direct, hands-on experience with Google Cloud Platform, especially BigQuery, Dataflow, GKE, Composer and Vertex AI. • Knowledge of Kubernetes concepts and experience running data services or pipelines on GKE. • Strong understanding of distributed systems, microservice patterns, and data‐centric system design. • Hands‐on experience working with ML/AI model integration in production (e.g., Vertex AI Endpoints, TensorFlow Serving, ML REST APIs). • Experience handling structured and unstructured datasets, including healthcare data (Rx claims, clinical documents, NLP text). • Familiarity with the end-to-end ML lifecycle: data ingestion, feature engineering, training, deployment, and real‐time inference. • Experience using Vertex AI, Kubeflow, or other ML orchestration platforms for model training and serving. • Knowledge of GenAI pipelines, LLM prompt workflows, and agent orchestration frameworks (e.g., LangChain, transformers). • Experience deploying Python-based ML/NLP services into microservice ecosystems using REST, gRPC, or sidecar architectures. • Domain experience in healthcare, claim adjudication, or Rx data processing.