Manager, Data Engineering

• Assist in new business development and technical sales through development of proposals, estimation, statements of work, and requests for proposals
• Contributing to and overseeing the successful delivery of data platform, analytics, and data science projects while liaising with clients to meet their needs
• Providing leadership, coaching, and mentorship to team members and supporting their professional development while establishing a learning culture
• Staying current on latest trends and technologies, while sharing expertise with colleagues, clients, and industry peers through speaking engagements, publications, and workshops
• Defining data roadmaps at the executive level for clients and detailed planning of data and AI governance frameworks
• Collaborating with project management to plan work for delivery teams and verifying quality deliverables

• Bachelor’s degree in computer science or related field
• 12 years of industry experience, with 4 most recent years as a hands-on manager leading a team on enterprise scale data platform projects
• 4 years of experience in a consulting role working directly with Enterprise customers
• Expertise with Microsoft Azure infrastructure and data resources, including Fabric, Azure Data Factory, Synapse Data Analytics, Power BI, Azure SQL, Azure Cosmos DB, and Azure Database for PostgreSQL
• Deep expertise with Databricks, specifically the ability to design enterprise-level strategy and architecture including Unity Catalog, data warehousing, data sharing, and Mosaic AI
• Experience setting end-to-end modern data platforms in Azure including architecture/design, ingestion, storage strategies, analytics & reporting, Apache Spark, and networking requirements
• Experience establishing data management strategy for customers, including data governance, data security, master data management, and familiarity with different industry security requirements
• Excellent communication skills, ability to clearly explain concepts to teammates and customers, and quickly learn new concepts and technologies

• Ability to create working environments for data engineers and scientists, and general knowledge of ML, AI, LLMs, and MLOps
• Knowledge and familiarity with Microsoft Purview
• DevOps for data, GitHub, automated testing, and working with containers (AKS, Docker, registries, etc.)
• Broad experience with data/reporting tools, architectures, cloud vendors, and data/AI concepts other than Microsoft
• Experience with industry leading data tools, such as Profisee, FiveTran, DBT, and Collibra

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.