Manager, Data and Analytics

Responsibilities

• Provide technical leadership and architectural direction to internal and vendor teams to deliver secure, scalable, and reliable enterprise data solutions
• Define, implement, and enforce enterprise data standards, including ingestion, transformation, data quality, and operational monitoring processes
• Lead, mentor, and develop a team of Data Engineers and Analytics Engineers, fostering a culture of engineering excellence and continuous improvement
• Establish team goals, manage performance, and support career progression through coaching and development planning
• Manage team capacity, prioritize workloads, and allocate resources across concurrent initiatives and operational needs
• Partner with business and analytics stakeholders to understand requirements, communicate progress, and manage expectations across projects
• Ensure data pipelines meet SLAs for availability, freshness, completeness, and accuracy
• Establish and maintain data quality frameworks, including monitoring, validation, and alerting strategies
• Lead root-cause analysis and resolution of complex data and platform issues across multiple systems
• Champion data governance practices, including metadata management, lineage, classification, and access control using Unity Catalog while ensuring compliance with data privacy standards
• Architect and evolve a modern Lakehouse platform leveraging Azure Data Lake Storage Gen2, Delta Lake, and medallion architecture (bronze/silver/gold)
• Enable advanced analytics and self-service BI by delivering curated semantic models and Power BI solutions
• Drive platform performance optimization and cost efficiency, including Databricks tuning, cluster management, and cloud cost governance
• Maintain comprehensive documentation, SOPs, and operational runbooks to support scalable and sustainable data platform operations

Qualifications

• Education: Undergraduate degree in Computer Science, Information Systems, Engineering, or a related technical field from an accredited college or university required; Graduate degree preferred
• Certification/Licensure: Relevant cloud or data certifications (e.g., Microsoft Azure Data Engineer Associate, Databricks certification) preferred
• Experience: 10+ years of experience designing and building enterprise data and analytics solutions using modern cloud technologies; 5+ years of experience leading technical teams, delivering multiple concurrent projects, and owning architecture and delivery quality; Proven experience building and scaling data platforms on Microsoft Azure, including Azure Databricks and ADLS Gen2; Strong expertise in Lakehouse architecture (Delta Lake, medallion design) and both batch and streaming data processing (e.g., Structured Streaming, Auto Loader, Event Hubs, Kafka); Experience delivering semantic models and self-service analytics solutions, including Power BI and dimensional modeling; Experience with DataOps practices, CI/CD pipelines, infrastructure-as-code (Terraform), and orchestration tools (ADF, Databricks Workflows, Airflow); Demonstrated ability to translate complex business requirements into scalable, reusable data products in partnership with stakeholders; Supply chain experience preferred; Demonstrated discretion and confidentiality in handling and protecting sensitive information
• Technical: Proficient with common office technologies, including Windows PCs, Microsoft O365 (Outlook, Word, Excel, PowerPoint, etc.) and web conferencing (Teams, Zoom, Webex, etc.)