Hiring a GCP Lead Data Engineer for Hyderabad, Chennai, Noida, Pune, and Bangalore locations
Role & responsibilities
10+ years of hands-on database experience, data engineering experience including relational databases, Bigquery and document databases
5+ years of cloud experience, preferably on Google Cloud Platform.
Strong experience with RDBMS technologies, including PostgreSQL, MySQL, SQL Server, Oracle, or equivalent relational database platforms.
Strong experience designing and implementing data pipelines, including batch, streaming, event-driven, and API-based processing patterns.
Strong programming experience, especially with Python, including object-oriented programming, modular application design, error handling, logging, unit testing, package management, and production-grade backend development.
Experience with Dataflow, Apache Beam, or equivalent data pipeline frameworks.
Experience integrating with external APIs, including authentication, retries, rate limits, error handling, and monitoring.
Docker and CI/CD experience.
Production monitoring, logging, alerting, and troubleshooting experience.
Experience with search systems such as ElasticSearch, OpenSearch, vector databases, or hybrid keyword/vector search systems.
Strong system design and architecture skills.
Ability to mentor mid-level and junior engineers.
Ability to create clear technical documentation, architecture diagrams, and implementation plans.
Preferred candidate profile
Design, build and support scalable healthcare data pipelines on GCP.
Process healthcare files from GCS and route them through Pub/Sub, Eventarc, Cloud Run, Dataflow, BigQuery, FHIR Store, and downstream systems.
Design relational and cloud database schemas for operational, analytical, and document-oriented workloads.
Build APIs to monitor pipeline status, file processing, Pub/Sub messages, Dataflow jobs, Cloud Run services, BigQuery loads, and FHIR data validation.
Design database models for pipeline metadata, orchestration configuration, processing history, audit logs, document metadata, and search indexes.
Implement batch and streaming data pipelines.
Build data validation, reconciliation, retry, and dead-letter handling processes.
Integrate structured, semi-structured, and unstructured healthcare data.
Support semantic search, NER, embeddings, and search result snippets for healthcare documents.
Optimize database performance, query cost, indexing strategy, and storage design.
Implement monitoring, logging, alerting, and operational traceability.
Ensure secure handling of healthcare data, including PHI-aware design and least-privilege access.
Mentor mid-level and junior engineers and define engineering best practices.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full time