Data Engineer - Sigma Team - Austin

Biorce is a health technology company using AI to accelerate drug development and improve patient outcomes. The Data Engineer will build and optimize scalable, reliable data pipelines on Google Cloud Platform, supporting clinical research products, analytics, machine learning, and regulatory-grade insights. The role also involves collaborating with product owners, data scientists, AI engineers, and DevOps teams to evolve the company’s data and AI architecture.

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

Support the Sigma portfolio end to end — building shared, reusable data foundations that serve multiple products rather than one-off pipelines per feature

Partner with Sigma product owners on prioritisation and sequencing, translating customer signals into data capabilities and flagging where data constraints shape what's feasible

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

Preferred

Experience with clinical, biomedical, or healthcare datasets

Familiarity with Vertex AI, AI Platform Pipelines, or ML metadata tracking

Understanding of data governance and cataloging, such as 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 or Docker

Experience implementing data validation frameworks, such as Great Expectations or TFX Data Validation

Experience working directly with product owners or customer-facing teams in a product-portfolio setting

Strong focus on reliability, observability, and continuous improvement of data systems

Clinical Data Experience

Biomedical Data Experience

Healthcare Data Experience

Vertex AI

AI Platform Pipelines

ML Metadata Tracking

Data Governance

Data Cataloging

Data Catalog

Looker

Apache Beam

Spark

dbt

Complex Data Transformations

Infrastructure as Code

Containerized Workflows

Kubernetes

Docker

Data Validation Frameworks

Great Expectations

TFX Data Validation

Product-Portfolio Experience

Product Owner Collaboration

Customer-Facing Experience

Data System Observability

Cross-Functional Collaboration

Reliability

Continuous Improvement

Benefits

A dynamic work environment with an international team, where collaboration and diversity thrive.

Work alongside top talent, united by a shared purpose and committed to making a real impact.

Direct visibility into the CSO's Office and the product decisions shaping Biorce's clinical research portfolio.

Comprehensive private health coverage to ensure your physical and mental well-being.

Hybrid work model offering flexibility to balance your professional and personal life.

Company events to celebrate achievements and enjoy time together.

Get equipped with a MacBook to enhance your productivity and work experience.

Our office is pet-friendly! You'll likely be greeted by a few wagging tails upon arrival.

Company

AI platform for clinical trial development

Barcelona, Catalonia, ESP

https://www.biorce.com/

Founded in 2024

201-500 employees

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, such as Terraform or GitOps

Experience working collaboratively with data scientists and MLOps teams

Comfort operating across several products or workstreams at once, with the judgement to prioritise where impact is highest

Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field

Experience with clinical, biomedical, or healthcare datasets

Familiarity with Vertex AI, AI Platform Pipelines, or ML metadata tracking

Understanding of data governance and cataloging, such as 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 or Docker

Experience implementing data validation frameworks, such as Great Expectations or TFX Data Validation

Experience working directly with product owners or customer-facing teams in a product-portfolio setting

Strong focus on reliability, observability, and continuous improvement of data systems

3+ years of professional experience in Data Engineering or related roles.

Required skills

BigQuery, Google Cloud Storage, Google Cloud Pub/Sub, Google Cloud Data Fusion, Google Cloud Dataflow, Cloud Composer, Google Cloud Functions, SQL, Python, Batch and Streaming Data Pipelines, Data Modeling, Terraform

Preferred skills

Experience with clinical, biomedical, or healthcare datasets

Experience

3+ years