The Lead Data Engineer will design, build, and operationalize scalable data solutions to support enterprise analytics and AI/ML initiatives. This role requires expert-level proficiency in Databricks, Azure Fabric, PySpark, SQL, and the Azure ecosystem, with deep experience across data warehouses, data lakes, and real-time integration. The Lead Data Engineer will architect end-to-end pipelines using industry-standard tools, drive automation, and move solutions effectively into production. The incumbent will ensure compliance with data governance requirements (including GxP and HIPAA/GDPR) while building reusable, integrated pipelines and analytical models that promote self-service analytics. This role provides technical leadership across the team, mentors junior engineers, and partners with business stakeholders to align data engineering with organizational objectives. ABOUT THE ROLE .  Data Architecture & Engineering * Architect, design, and implement end-to-end data solutions using Azure Databricks, PySpark, Azure Data Factory, and Azure SQL. * Design, build, and maintain data pipelines from data sources through integration to consumption for specific use cases. * Implement robust data modeling standards across bronze, silver, and gold layers in the data lake. * Develop data models (conceptual, logical, and/or physical) as required. * Optimize Spark and SQL workloads for performance, scalability, and cost efficiency. * Manage metadata using data preparation, integration, and AI-enabled tools and techniques.   .  Data Integration & Automation * Drive automation in data integration; recommend and lead implementation of techniques to automate repeatable data preparation and integration tasks. * Build API-based integrations (REST/JSON) and real-time ingestion frameworks. * Automate data workflows using Azure DevOps pipelines and Git-based CI/CD practices. * Implement parameterized, reusable pipeline templates for ingestion and transformation. * Develop automated unit, regression, and integration testing frameworks for data jobs.   .  Analytics & Data Enablement * Prepare and curate high-quality datasets for BI, reporting, and advanced analytics. * Partner with analytics teams using Power BI, Tableau, or similar platforms to define semantic models and KPIs. * Implement performance-optimized data models for self-service analytics. * Will occasionally provide support to end users on the use of data visualization solutions.   Stakeholder Engagement & Leadership * Lead technical design reviews, mentor junior engineers, and promote best practices. * Assist cross-functional groups, business analysts, and stakeholders to gather, define, and refine data requirements. * Collaborate with business and IT stakeholders to align data engineering with organizational objectives. * Propose innovative data ingestion, preparation, and integration techniques to address stakeholder requirements. * Contribute to architectural roadmaps and technology evaluations for the data platform. * In collaboration with functional leaders, identify inefficiencies and recommend improvements to the executive team. ABOUT YOU Job Experience & Education Requirements: Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (Master’s preferred) And 5–8 years of experience designing and developing enterprise-scale data solutions (data warehouses, data lakes, operational databases)   Other: * Expert-level proficiency in Databricks, Azure Fabric, PySpark, SQL, and Azure DevOps. * Proven experience with Azure Data Factory, ADLS Gen2, and Azure SQL Server. * Strong experience with Microsoft Azure data management architectures including Data Warehouse, Data Lake, and Data Catalogue, and supporting processes such as Data Integration, Governance, and Metadata Management. * Experience with Power BI required; Tableau or Looker a plus. * Working knowledge of CI/CD automation, version control (Git), and infrastructure as code (ARM, Bicep, or Terraform). * Experience in life sciences or healthcare industries is a strong plus. * Good understanding of GxP, GDPR/HIPAA, and applicable CFR/CTR/CTD regulations. * Demonstrated success working with both IT and business stakeholders while integrating analytics and data science output into business processes and workflows. * Must have excellent written and verbal communication skills. * Proven ability to work independently and as part of a team and meet important deadlines. * Statistical analysis skills are an asset.