Tech Advisory, Data Engineering Manager

Crowe is a leading public accounting, consulting, and technology firm that emphasizes innovation and client service. They are seeking a Data Engineering Manager to lead data platform engagements, combining technical expertise with project management and client advisory responsibilities.

Responsibilities:

• Lead end-to-end delivery of data engineering engagements, owning scope, quality, timeline, and client satisfaction
• Conduct discovery workshops to assess current-state data architectures, integration patterns, and platform maturity
• Author and present statements of work, technical proposals, and executive-level deliverables
• Serve as the senior escalation point for architectural decisions and complex technical issues across active engagements
• Design and implement scalable data pipelines, ingestion frameworks, and transformation layers using both platforms such as Microsoft Fabric, Databricks, and MuleSoft, as well as
• Write, review, and optimize production code in Python, SQL, and/or Scala; enforce code quality standards and best practices across the engagement team
• Architect cloud environments and govern data modeling decisions
• Evaluate and recommend vendor solutions aligned to client use cases, data volumes, and existing technology landscape
• Integrate structured and unstructured data sources, including APIs, event streams, and enterprise applications
• Manage and mentor team members, providing technical guidance and career development support
• Collaborate with client executive, data, analytics, and IT teams to align delivery priorities and ensure adoption of engineered solutions
• Coordinate across workstreams (M&A, Integrations, Data Governance, Analytics, Cloud Infrastructure) to ensure cohesive platform delivery
• Contribute to the development of reusable accelerators, delivery playbooks, and platform standards within the practice
• Support business development activities including RFP responses, capability demonstrations, and client presentations
• Stay current on emerging data engineering tools, frameworks, and vendor roadmaps; share knowledge across the practice

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or related field
• 5–8+ years of progressive experience in data engineering, data platform development, or technical consulting
• Demonstrated experience leading data platform builds, migrations, or integration programs in a client-facing or consulting environment
• Prior experience managing or mentoring technical team members
• Strong proficiency in Python
• Strong proficiency in SQL
• Microsoft Fabric (Lakehouse, Data Factory, Synapse Analytics, Real-Time Intelligence)
• Databricks (Delta Lake, MLflow, Unity Catalog, Spark)
• MuleSoft (Anypoint Platform, API-led connectivity, DataWeave)
• Microsoft Azure (Data Lake Storage, Azure Data Factory, Azure SQL, Synapse)
• REST APIs, event-driven architectures, ETL/ELT pipelines, message queues (Kafka, Event Hubs)
• Familiarity with data cataloging, lineage, and quality frameworks (Purview, Unity Catalog, or similar)
• Strong analytical thinking and structured problem-solving capabilities
• Able to translate complex technical concepts into clear business value for non-technical stakeholders
• Executive presence with experience engaging Director- and C-suite-level client contacts
• Collaborative leadership style with a track record of developing junior and offshore talent
• Comfortable managing multiple concurrent engagements in a fast-paced professional services environment
• Detail-oriented with strong written and verbal communication skills
• Microsoft Certified: Fabric Analytics Engineer Associate or Azure Data Engineer Associate
• Databricks Certified Data Engineer Associate or Professional
• Private Equity or Financial Services sector experience
• Scala or Spark proficiency
• AWS or GCP exposure