Overview

You will take on a hands on technical leadership role where you design the platform architecture, drive engineering decisions, and guide a small team. You will be responsible for building end to end data pipelines, shaping the canonical data model, and ensuring the platform delivers high quality and well structured clinical data to product and analytics teams. Project Overview: You will work on a modern clinical and real world data platform that brings together EHR, EDC, lab data, and registries into a shared clinical data model. The goal is to build a scalable environment on Databricks with reusable data pipelines, semantic layers, and strong data quality foundations.

Responsibilities:
  • Design and develop the Databricks based data platform and reusable pipelines for ingestion, transformation, and data delivery
  • Design PoC solutions and validate ideas on real clinical datasets
  • Define and maintain clinical and canonical data models for priority domains
  • Build and improve the semantic layer and ontologies including concepts, metrics, and mappings
  • Implement and automate data quality rules and monitoring within all pipelines
  • Lead and mentor a small group of data engineers and review designs and code
  • Set engineering standards and guide technical decisions
  • Collaborate with product teams, clinical experts, data scientists, and BI specialists to clarify needs and priorities
Required Qualifications:
  • Seven years of experience in data engineering or data architecture with production pipelines
  • Strong experience working with Databricks including Spark, Delta Lake, jobs, and performance tuning
  • Experience designing canonical or domain data models preferably for clinical or healthcare data
  • Experience working with ontologies or semantic layer design
  • Practical experience implementing data quality rules and frameworks in pipelines
  • Experience leading or mentoring engineers and driving technical decisions
  • Strong communication skills and effective stakeholder collaboration
  • Domain knowledge in clinical research, healthcare, or pharma tech
Nice To Have:
  • Familiarity with clinical data standards such as FHIR, CDISC, or OMOP
  • Knowledge of medical terminologies
  • Experience with semantic web or knowledge graph technologies
  • Experience working in international distributed teams
Note:

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