Director, Data Engineering

Required Skills & Experience 10 years of experience in data engineering, data architecture, or related fields within enterprise environments\n\n5+ years of experience of management experience, leading data engineering teams or technical teams\n\nStrong background with cloud data platforms, data warehousing, and large-scale data pipeline development\n\nStrong cloud experience is a must have. Azure experience preferred, with Microsoft Fabric being a big plus\n\nHands-on experience with ETL/data integration tools such as Azure Data Factory, AWS Glue, Boomi, or similar\n\nStrong SQL and Python skills\n\nExperience with modern data frameworks and technologies including Spark, Airflow, and Kafka\nKnowledge of data modeling, data integration, data quality, and enterprise data warehousing\n\nFamiliarity with AI/ML data enablement and supporting analytics and reporting initiatives\n\nStrong communication skills with the ability to partner effectively with both technical and non-technical stakeholders\n\nBachelor's degree required, Master's degree preferred Job Description Reporting to the VP of Enterprise Data & Analytics, this Director of Data Engineering will lead the data engineering function while helping define and execute the organization's long-term data roadmap. The role is focused on scaling cloud-based data platforms, modernizing data infrastructure, supporting AI initiatives, and ensuring the organization has reliable, accessible data for reporting, analytics, and business decision making. They will manage a team of around 10-11 with one manager, with opportunity to grow dependent on roadmap and needs. Daily responsibilities include:\n\nLead the Data Engineering function, overseeing enterprise data platforms, pipelines, and cloud-based data architecture\n\nHelp define, develop and execute the teams data roadmap and long-term strategy\n\nCollaborate with BI and analytics leaders to improve data quality, reporting capabilities, and enterprise data models\n\nDrive cloud data strategy and modernization efforts across Azure, Microsoft Fabric, enterprise data warehouses, and data pipeline architecture.\n\nSupport and scale AI-enabled data initiatives, including AI-assisted ETL, data ingestion, and automation\n\nWork cross-functionally with business and technical stakeholders, translating business needs into data solutions\n\nSome initiatives include:\nSupporting integration projects, including HR data, EMR integration, and upcoming financial system updates\n\nIncrease AI across department and organization, with goal to use AI end to end for data quality, automation, code reviews, ETL optimization, and data cleanup standardization\n\nImprove visibility with patient data tracking (accurately capturing data post service) Insight Global