You’ll work closely with data scientists, AI engineers, and devops to design and operationalize robust data flows that fuel advanced analytics, machine learning, and regulatory-grade insights.

This is an exciting opportunity to build and optimize the data backbone of Biorce’s next-generation platform, using modern GCP-native tools such as Data Fusion, BigQuery, and Cloud Storage, in a high-impact, fast-iterating environment.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using Google Cloud Data Fusion, Dataflow, Pub/Sub, and BigQuery.
• Build and orchestrate complex data ingestion workflows from diverse clinical, research, and third-party sources.
• Collaborate with data scientists to enable seamless model training, feature generation, and inference data flows.
• Ensure data quality, integrity, and lineage across all systems through rigorous validation and monitoring.
• Develop and optimize SQL and Python-based transformations to ensure high performance and maintainability.
• Manage data storage, partitioning, and lifecycle strategies for efficiency and cost control.
• Ensure compliance with SOC2, ISO 27001, HIPAA, GDPR, and clinical data governance standards in all data operations.
• Continuously improve internal frameworks for ingestion, metadata management, and data documentation.
• Contribute to cross-functional discussions to shape the evolution of Biorce’s data and AI architecture.

Required Qualifications

• 3+ years of professional experience in Data Engineering or related roles.
• Proven hands-on experience with GCP data tools:
• BigQuery, Cloud Storage, Pub/Sub, Data Fusion, Dataflow, Composer, and Cloud Functions.
• Strong proficiency in SQL and Python for data transformation and automation.
• Experience designing batch and streaming data pipelines with scalable and fault-tolerant architectures.
• Familiarity with data modeling, schema design, and data warehouse optimization.
• Understanding of API-based ingestion, data normalization, and pipeline monitoring.
• Exposure to version-controlled, modular pipeline development (e.g., Terraform, GitOps).
• Experience working collaboratively with data scientists and MLOps teams.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.

Preferred Qualifications

• Experience with clinical, biomedical, or healthcare datasets.
• Familiarity with Vertex AI, AI Platform Pipelines, or ML metadata tracking.
• Understanding of data governance and cataloging (Data Catalog, Looker, or similar).
• Knowledge of Apache Beam, Spark, or dbt for complex transformations.
• Exposure to infrastructure-as-code (Terraform) and containerized workflows (Kubernetes, Docker).
• Experience implementing data validation frameworks (e.g., Great Expectations, TFX Data Validation).
• Strong focus on reliability, observability, and continuous improvement of data systems.

Why Join Us?

• Build the data foundation powering AI innovation in healthcare.
• Work closely with world-class data scientists and AI engineers on cutting-edge use cases.
• Be part of a team that values continuous iteration, experimentation, and data excellence.
• Comprehensive private health coverage to ensure your physical and mental well-being.
• Company-sponsored gym membership and wellness benefits.
• Hybrid work model offering flexibility to balance your professional and personal life.
• Coffee, tea, beverages, and snacks to keep you fueled throughout the day.
• Company events to celebrate achievements and foster team spirit.
• Get equipped with a MacBook laptop and top-tier GCP tools to maximize your impact.