Databricks Data Architect (Healthcare & Life Sciences)

About Entrada AI Entrada AI is a specialized consulting partner and a strategic portfolio company of Databricks Ventures. We were recently named the Genie Partner of the Year (2026) for our work deploying Databricks Genie at enterprise scale—bridging the gap between AI ambition and the trusted, governed data required for accurate responses. With over 150 Databricks projects delivered, we unlock self-service analytics for Fortune 500 leaders.

Databricks invested in us because of our technical excellence, placing us in the "inner circle" of the ecosystem. For our engineers, this means direct access to product roadmaps, private previews, and the teams building the platform. You will join a team of industry veterans who value clean architecture over quick fixes. We don't just maintain pipelines; we solve complex architectural challenges.

About the Role Entrada AI, Inc. is seeking an experienced Databricks Data Architect with a specialized background in Healthcare and Life Sciences (HLS) to join our consulting team. In this role, you will lead the design and implementation of modern Lakehouse architectures for organizations ranging from health systems and payers to biopharma and medical device companies.

You will be responsible for defining how sensitive clinical, operational, and research data is stored, governed, and analyzed. You will work at the intersection of technology and medicine, ensuring that our data systems are not only scalable and performant but also meet the highest standards of security and regulatory compliance (HIPAA, GxP, GDPR).term AI strategy.

Key Responsibilities AHLS Data Strategy: Design and oversee the development of Databricks-based Lakehouse architectures tailored for healthcare use cases, such as Real-World Evidence (RWE), clinical trial optimization, and population health management. Interoperability & Integration: Define strategies for ingesting and transforming complex healthcare data types, including HL7, FHIR, EDI, and OMOP Common Data Models.

Governance & Compliance: Implement robust data governance frameworks using Databricks Unity Catalog - catalog design, data classification and tagging, lineage, and audit logging - to meet HIPAA and GDPR obligations for PHI and to protect client intellectual property. Collaboration: Work closely with data scientists, and clinical researchers to translate complex biological or operational requirements into scalable technical solutions.

Optimization: Architect high-performance pipelines for large-scale healthcare datasets (e.g., longitudinal patient records, genomic sequences, or claims data) ensuring cost-efficiency and speed. Security Design: Design and implement sophisticated access controls, data masking, and encryption protocols to protect Protected Health Information (PHI) and Intellectual Property (IP).

Technical Leadership: Provide mentorship to data engineers on HLS best practices, including the use of Delta Lake for maintaining audit trails and data versioning. Documentation: Maintain rigorous documentation for validated environments, including data lineage, system architecture, and compliance-related design specifications. Requirements Education: Bachelor’s or Master’s degree in Computer Science, Bioinformatics, Health Informatics, or a related field.

Experience: 5+ years of experience in data architecture or data engineering, with at least 2+ years specifically within the Healthcare or Life Sciences domain. Databricks Mastery: 3+ years hands-on Databricks, including at least one platform you architected and stood up from the ground up: Unity Catalog metastore and catalog/schema design, external locations and storage credentials, cluster policies and compute governance, cost controls, and secure networking (Private Link or VNet/VPC injection, no-public-IP, storage firewall rules).

HLS Knowledge: Deep understanding of healthcare data privacy regulations (HIPAA/GDPR) and familiarity with healthcare data standards (FHIR, HL7, or OMOP). Cloud Platforms: Proficiency in cloud environments (Azure, AWS, or GCP), particularly in high-security/"walled garden" configurations. Big Data Tech: Experience with Spark, Python, SQL, and orchestration tools (e.g., Airflow, Azure Data Factory).

Soft Skills: Excellent communication skills, with the ability to explain complex technical architectures to non-technical clinical stakeholders. Nice to Have (Medical Imaging Experience) Medical Imaging Expertise: Experience architecting solutions for Medical Imaging (DICOM, NIfTI) data. Imaging Pipelines: Familiarity with integrating PACS/VNA systems with cloud data lakes or using Databricks to process pixel data for AI/ML model training.

Clinical AI: Experience supporting computer vision projects for radiology, pathology, or ophthalmology. Certifications: Databricks Certified Solutions Architect or Cloud-specific Health Data certifications. The Offer Cooperation Models : Poland: Available via Employment Contract (UoP) or B2B. Romania/ Greece: Available via B2B only. 100% Remote : Full flexibility to work from anywhere in Poland/ Romania / Greece High-End Tech : Apple MacBook Air M4 15" provided to all engineers.

Referral Bonus : Bonus for bringing other top-tier engineers to the team. Professional Growth : Certification Support : Coverage for all Databricks technical certifications. Industry Leadership : Support in reaching the highest tiers of Databricks expertise (such as the Champion program) tailored to your specific career track. Personal Branding : Opportunities to present at global industry conferences and contribute to technical thought leadership.

Expert Mentorship : Direct collaboration with Databricks MVPs and core product teams, giving you a front-row seat to the platform's evolution. Recruitment Process Introductory Call (20 min) : Short conversation with our Recruiter to discuss your background and expectations. Technical Interview (60 min) : Deep dive into your technical skills with our engineering team.

Optional Client Interview : Required only in specific cases. Decision & Offer : We aim to close the process and provide feedback efficiently.