Manager, Data Engineering

Responsibilities

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

Minimum Requirements

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

Preferred Qualifications

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