Data Architect

Hands-on experience designing and building enterprise data solutions on Google Cloud Platform or another major cloud provider — with a portfolio of systems personally built, not only specified.

 Must-have skills/tools:

 Python and SQL at production depth; JVM-based languages (Java/Scala)

 BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer

 Pub/Sub, Kafka, Spark Streaming

 Cloud Run, GKE, Cloud Functions

 Lakehouse formats: Iceberg, Delta Lake, Parquet, Avro, JSON

 CI/CD pipelines, Git/GitHub, test-driven development

 Nice-to-have skills/tools:

 Terraform, Docker, Kubernetes, Dynatrace

 Bigtable, Cloud SQL, Cloud Spanner

 Microservices architecture, OpenAPI/REST and event-driven API design

 Vertex AI, LangChain, embeddings, RAG patterns

 Healthcare domain knowledge/experience

 Experience with document and unstructured data processing, including ingestion, enrichment, and indexing.

 Practical experience integrating LLMs and AI frameworks into production data pipelines.

 Strong understanding of data security, privacy, and regulatory requirements (HIPAA, GDPR) in cloud environments.

 Strong ability to assemble large, complex data sets meeting functional and non-functional requirements.

 Strong ability to identify, design, and implement internal process improvements, including redesigning data platforms for greater scalability and optimized data delivery.

 Expert ability using source control management and CI/CD automation tools.

 Strong understanding of Agile methodologies and how to apply Agile within the team.

 Ability to communicate complex architectures clearly to both technical and non-technical audiences, and to present and facilitate technical ideas.