Senior Manager - Data Engineering (Databricks)

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The Senior Manager, Data Engineering is a strategic leader responsible for overseeing a Data Engineering team to drive the efficient use of data across the organization. This role involves developing and executing a comprehensive data strategy, ensuring robust and scalable data infrastructure, and aligning data initiatives with business objectives. Key responsibilities include managing complex project timelines, optimizing data systems for performance, and ensuring the reliability of data pipelines. This position requires strong leadership, excellent communication, and problem-solving skills, with a focus on mentoring and developing talent within the team. The ideal candidate has extensive experience in data engineering, a deep understanding of relevant technologies, and a proven track record in managing diverse teams. This role is crucial in advancing the organization's data capabilities and supporting its strategic goals.

Essential Job Functions:

• Lead, coach, motivate, challenge and provide managerial guidance to the team. Develop and execute training programs and career development plans for the teams and individual associates. Utilize excellent communication skills to articulate a strategic vision to the team. Solve problems and make decisions with sound judgement. - (20%)
• Provide continuous feedback and completes formal performance evaluations as directed by the organization. Value associate recognition and celebrating the accomplishments of individual team members as well as the overall team. Lead both direct reports and other associates to accomplish company initiatives. - (15%)
• Continuously assess and integrate emerging technologies and industry trends to enhance the data engineering team's efficiency and innovation capabilities. Gain domain knowledge of the data sources and associated business processes ingested by the Data Engineering team. Act as subject matter expert in projects and initiatives throughout the enterprise. - (15%)
• Use various technologies and tools to analyze source data, perform QA analysis and debug possible data quality issues. May use technologies such as SQL, Hadoop, Spark, SAS, R, Python, etc. Monitor jobs and data pipelines for possible issues. Understand high-level functionality of many technologies and is able to navigate systems and help identify root causes. - (15%)
• Act as an internal and external-facing liaison for Data Engineering. Ensure data ingestion projects adhere to Bread Financial policies and procedures, such as data governance, information security, data retention, etc. Demonstrates outstanding verbal and written communication skills when working with internal and external partners. - (10%)
• Prioritize efforts on critical initiatives and works to identify opportunities and problem solve. Utilize critical thinking skills to help analyze business issues, collaborates with stakeholders to resolve problems, and gains consensus on the best solution. - (10%)
• Ensure data security and compliance with relevant regulations (e.g., GDPR, CCPA) and internal policies. Develop and implement data security measures to protect sensitive information. Identify potential risks in data engineering processes and develop strategies to mitigate them, ensuring continuity and reliability of data services. - (15%)

Minimum Qualifications:

• Bachelor's Degree in Computer Science, Mathematics, related technical field or equivalent practical experience.
• 1 cloud certification - AWS Cloud Practitioner, Microsoft Azure Fundamentals or Google Cloud - Cloud Digital Leader
• 10-13 years of experience across data analysis, cloud data platform architectures and infrastructure platforms such as Azure or AWS, SQL queries, support of Big Data and Analytics development.
• 3+ years of leadership experience.

Preferred Qualifications:

• Master's Degree in Computer Science, Mathematics, or related field of study.
• 13-15 years of project management, data governance, data management, associate engagement and career planning.
• 5+ years of leadership experience

Work Environment:

Normal office environment, hybrid.

Skills

AWS, Azure, Data Engineering, Databricks