The Senior Manager, Data Engineering will play a pivotal role in driving data-driven decision-making and innovation within our organization. This high-impact position requires a seasoned leader with a deep understanding of data engineering principles, cloud technologies, and a proven track record of delivering complex projects.


Responsibilities

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  Technical Leadership: Oversee the design, development, and maintenance of data infrastructure, pipelines, and systems that support critical business operations.


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  Team Management: Lead, mentor, and develop a high-performing team of data engineers, ensuring they have the tools, resources, and support needed to succeed.


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  Technology Modernization: Drive the adoption of modern data technologies and best practices to enhance efficiency, scalability, and reliability.


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  Stakeholder Management: Build and maintain strong relationships with business leaders, IT stakeholders, and vendors to align data initiatives with strategic objectives.


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  Project Delivery: Successfully manage data engineering projects, from planning and execution to delivery, ensuring they meet timelines, budgets, and quality standards.


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  Data Governance: Establish and enforce data governance policies and standards to ensure data quality, security, and compliance.


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  Innovation: Foster a culture of innovation by exploring new data technologies and techniques to drive competitive advantage.

• Bachelor's degree in Computer Science, Data Engineering, or a related field.


• 8+ years of experience in data engineering or related roles.


• 4+ years of experience managing teams and vendors.


• Proven track record of delivering successful data engineering projects.


• Deep understanding of database design, data modeling, and ETL processes.


• Expertise in cloud platforms (e.g., Azure, AWS, GCP) and cloud-native data technologies.


• Strong organizational, problem-solving, and decision-making skills.


• Excellent communication and interpersonal skills.


• Ability to thrive in a fast-paced, dynamic environment.

• Experience with specific data engineering tools and technologies (e.g., Data Lake, Azure Data Factory, Synapse) would be a plus.


• A strong understanding of data privacy and security regulations is beneficial.


• A passion for data and a drive to extract insights to drive business outcomes is essential.