Sr. Director, Data Engineering + Integrations

Prolaio • Chicago, IL

6d

About The Position

The Director/Sr. Director, Data Engineering will lead and scale Prolaio’s healthcare data engineering capabilities that power its clinical intelligence products, real-world data pipelines, analytics, data science, clinical operations, quality, and data services in a regulated environment, building secure, reliable, and AI-enabled data platforms that transform continuous, predictive, and shareable heart data into faster therapeutic discovery and better cardiovascular outcomes while operating as a self-starter senior leader in a growth-stage company. This role will ensure that core data engineering features and services are built with security, privacy, compliance, and auditability by design, and other regulatory expectations relevant to Prolaio’s clinical and patient-data environment. This role will partner with colleagues in Product, Engineering, Quality, Clinical Operations to embed security, privacy, HIPAA and regulatory expectations into every layer of the data engineering features. This is a role for a self-starter and experienced engineering leader who brings both organizational leadership and strong technical credibility in designing, building, and continuously enhancing data engineering and AI-enabled data pipeline features in a growth-stage company.

Requirements

• Bachelor’s degree in computer science, Data Engineering, Information Systems, Biomedical Informatics, Engineering, or a related field.
• Minimum 15 years of experience in healthcare, medtech, life sciences, digital health, or another patient-focused environment, with meaningful responsibility for data platforms, platform engineering, or cloud-native enterprise platforms.
• At least 7 years of experience as a Director or Sr. Director (or equivalent senior leadership role) leading data engineering or closely related data platform teams in growth-stage or innovation-driven organizations.
• Demonstrated experience architecting and delivering healthcare data platforms that support structured, semi-structured, and unstructured data, with proven success in regulated or validated environments.
• Deep understanding of healthcare data domains (clinical trials, cardiovascular and physiological data, real-world data, claims, medication, socio-economic and behavioral data) and the application of healthcare terminologies and common data models (e.g., HL7, FHIR, ICD, SNOMED CT, LOINC, RxNorm, OMOP, CDISC).
• Proven experience designing and operating end-to-end data flows, scalable pipelines, lineage, provenance, traceability, and data lifecycle management that support product, analytics, data science, clinical operations, quality, and data services use cases.
• Strong familiarity with cloud platforms such as GCP, AWS, or Azure and modern data platforms such as Snowflake, Databricks, BigQuery, Redshift, Synapse, or comparable environments, including hands-on work with orchestration, APIs, and integration.
• Strong software engineering and data engineering experience with Python and SQL and at least one of Java or .NET, with a track record of building internal data platform features, services, and developer tooling.
• Demonstrated ability to work effectively in cross-functional, matrixed organizations, partnering with Product, Engineering, Data Science, Analytics, Clinical Operations, Quality, and Security, with a self-starter mindset and comfort with ambiguity in a growth-stage environment.
• Familiarity with metadata, lineage, catalog, governance, and AI-enablement tools, including platforms for semantic indexing, vectorization, retrieval, and data lifecycle automation, and experience implementing governed data access and privacy-aware architectures.

Nice To Haves

• Experience with modern front-end frameworks (e.g., Angular or React) is good to have.
• Experience in developing Agentic pipelines would be a plus.

Responsibilities

• Lead Prolaio’s enterprise data engineering strategy and roadmap to deliver secure, scalable, and reliable data platform capabilities aligned to clinical, research, product, and AI priorities in regulated healthcare settings.
• Architect and oversee end-to-end data flows and reusable pipelines for ingestion, validation, transformation, enrichment, publishing, retention, archival, and decommissioning across batch, streaming, and hybrid workloads.
• Own the design and implementation of scalable, secure, and interoperable data platforms that support structured, semi-structured, and unstructured clinical, operational, device, and patient-generated data relevant to Prolaio’s cardiovascular mission.
• Define and enforce engineering standards for data modeling, lifecycle management, lineage, provenance, traceability, and auditability, embedding HIPAA, privacy, security, and GxP-aligned practices into day-to-day development workflows.
• Partner closely with Data Architecture to design and govern conceptual, logical, and physical data models, apply healthcare standards (e.g., HL7, FHIR, ICD, SNOMED CT, LOINC, RxNorm, OMOP, CDISC), and deliver analysis-ready, interoperable datasets.
• Build and evolve robust data engineering capabilities across modern cloud platforms (e.g., GCP, AWS, Azure) and data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift, Synapse), including orchestration, metadata, APIs, and integration patterns.
• Lead the development of AI-enabled data engineering features such as intelligent data quality monitoring, metadata enrichment, semantic search, feature generation workflows, and automation that accelerate analytics, data science, and clinical research teams.
• Collaborate with Quality, Clinical Operations, Security, Product, and Engineering to embed validation, change management, governed data access, master data management, and release readiness into the data platform lifecycle.
• Establish and manage high-performing data engineering teams, providing clear ownership, coaching, and execution discipline suited to a fast-moving growth-stage environment, while influencing architecture and implementation decisions across a matrixed organization.
• Support vendor and tool evaluation, including build-versus-buy decisions for data integration, quality, metadata, lineage, interoperability, and AI-enabled data management capabilities.

Benefits

• Competitive salary
• performance bonus
• equity
• Medical, dental, and vision plans with multiple options and strong company contributions.
• HSA, FSA, commuter benefits, and a $1,200 annual Lifestyle Spending Account
• Generous paid time off, sick leave, and company holidays.
• Paid parental leave, caregiver leave, and support for growing families.
• Company-paid life insurance and short- and long-term disability coverage.
• 401(k) plan

What This Job Offers

• Job Type: Full-time
• Career Level: Director