Data Engineering Manager

• Provide strategic and operational leadership for data project teams comprised of technical and business teams delivering complex, business-critical applications, ensuring alignment with enterprise strategy and measurable business outcomes. Responsible for championing, orchestrating, budgeting, and directing multiple projects and initiatives simultaneously and removing impediments when necessary. Provide decision making, technical oversight, and prioritization guidance to project teams.
• Accountable for end-to-end delivery, technical direction, and performance of portfolio initiatives, including prioritization and execution excellence. Responsible for resource management of data teams by motivating, coaching, empowering, and fostering a culture of innovation and risk taking for colleagues. Facilitate the continual growth of colleagues by participating in the creation and execution of personal development plans focused on advancing data solutions and technical excellence and strong emotional intelligence. Responsible for resource allocation for projects in collaboration with business and technology leaders. Collaborate, coordinate, and negotiate with the data office to develop technical roadmaps in order to achieve strategic and tactical direction. Oversee implementation of technology strategies by ensuring alignment of projects with strategic direction while adhering to standards and best practices. Lead the evolution of engineering capabilities through modern practices (cloud, DevOps, AI-assisted development) while building high performing teams and fostering a culture of innovation, accountability, and continuous improvement. Build and maintain excellent relationships with business leaders. *

Additional Skillsets:

Focus on speed of delivery without compromising quality, security and integrity of each system designed or implemented.

Coach and mentor each team member and foster an environment of innovation.

Data Engineering Manager provides strategic, technical, and operational leadership for data engineering teams and a portfolio of complex, business-critical data platforms and initiatives, ensuring delivery aligns with enterprise strategy, measurable business outcomes, security, quality, and regulatory standards. This role directs architecture and engineering practices, resource and budget planning, vendor relationships, system performance and resiliency, and the adoption of cloud, DevOps/DataOps, automation, and AI-assisted engineering capabilities, while recruiting, coaching, and developing a high-performing team and partnering with business and technology leaders on data roadmaps and investment decisions. Qualified candidates will have a bachelor’s degree in computer science or a related field, or commensurate experience, including substantial technical experience and prior team leadership or management responsibility; advanced knowledge of data warehouse and operational data store design, master data management, relational and dimensional data modeling, SQL and query optimization, ETL/ELT, APIs, CI/CD and Git, information architecture, Snowflake, Informatica, Azure data technologies, cloud and enterprise security concepts, and AI/ML applications; and strong business acumen, communication, collaboration, project management, analytical problem-solving, and people-leadership skills., Must have the ability and commitment to provide effective feedback and conduct performance evaluations for individual team members. This includes goal setting, clear communication of performance expectations, ability to assess employee performance objectively, coaching as necessary and the ability to recognize employees.

Strong ability to foster necessary cross team collaboration, with both technical and non technical teams, to meet organizational goals and exceed customer expectations.

Promotes innovative and creative thinking

Proven commitment to meeting organizational, divisional and departmental strategies, goals, objectives, and standards

Advanced experience in the design, development, implementation and support of Data Warehouse, Operational Data Stores, and Master Data Management system

Expert understanding of database concepts (relational, multi-dimensional, hierarchical, etc.), data modeling concepts (dimensional/snowflake), SQL, query optimization, data warehouse architecture.

Significant experience providing technical design review, development plan critique, code review, test plan/results review

Familiarity with DataOps and DevOps practices, CI/CD pipelines for data solutions, and version control using Git.

Understanding of concepts and principles of Application Programming Interfaces (API) and RESTful data access patterns.

Familiarity with Azure SQL Managed Instances, Azure Synapse Analytics, Azure Data Factory,

Strong understanding and ability to apply machine learning/artificial intelligence concepts to solve business challenges

Strong understanding of cloud technologies and their application to the organization

Strong understanding of enterprise level security concepts and their implementations

Significant experience with data analysis and ETL/ELT processes.

Strong leadership, communication and collaboration skills to enhance interactions with all levels of personnel from technical to executive management to convey technical concepts and assist in messaging about support or design issues.

Ability to coordinate across multiple infrastructure groups and assist in deployment planning.

Experience with information architecture.

Experience in managing project teams through all phases of the project lifecycle from scoping and planning, requirements gathering, design, development, testing, and go live.

Strong project management skills leveraging industry standard development methodologies (e.g. Agile, etc.)

Ability to develop colleagues through coaching, mentoring and various management techniques.

Demonstration of a high level of administrative competence in resource management and reporting

Strong analytical and problem-solving skills