GCP Data Engineer

Role Focus (as clarified)

• Primary priority: Cloud Data Engineering on GCP
• Core skills: Dataflow DAGs/Composer Python Scala
• ML: Nice to have / bonus (not a must have)

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.
• 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.
• 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.
• 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.