What are the responsibilities and job description for the Sr. Manager Data Engineering position at Global Payments Inc.?
Description
The Senior Manager of Data Engineering leads and oversees a team of data engineers, responsible for designing, building, and maintaining large-scale data pipelines and infrastructure, ensuring data quality, scalability, and accessibility to support data-driven decision making within an organization, requiring a deep understanding of data engineering technologies, strong leadership skills, and the ability to collaborate with cross-functional teams to align data strategies with business objectives.
Key Responsibilities:
The Senior Manager of Data Engineering leads and oversees a team of data engineers, responsible for designing, building, and maintaining large-scale data pipelines and infrastructure, ensuring data quality, scalability, and accessibility to support data-driven decision making within an organization, requiring a deep understanding of data engineering technologies, strong leadership skills, and the ability to collaborate with cross-functional teams to align data strategies with business objectives.
Key Responsibilities:
- Manage and mentor a team of data engineers, assigning tasks, providing technical guidance, and driving career development.
- Architect and implement scalable data pipelines, data lakes, and data warehouses utilizing cloud technologies (AWS, Azure, GCP) to handle large volumes of data.
- Collaborate with stakeholders across the organization to identify data needs, define data strategy, and prioritize data engineering projects.
- Ensure the team adheres to best practices for data quality, data governance, and data security.
- Monitor data pipeline performance, identify bottlenecks, and optimize data processing efficiency.
- Research and implement new data engineering tools and technologies to stay current with industry trends.
- Lead data engineering projects from conception to deployment, including budget and timeline management.
- Work closely with data scientists, product managers, and business analysts to ensure data is readily available for analysis and decision-making.
- Strong proficiency in data engineering technologies such as SQL, Python, Spark, Hadoop, Kafka, and cloud data warehousing solutions.
- Deep understanding of data modeling, data warehousing concepts, and distributed data processing systems.
- Proven ability to lead and motivate high-performing teams, fostering collaboration and innovation.
- Excellent communication skills to effectively convey complex technical concepts to both technical and non-technical stakeholders.
- Ability to troubleshoot technical issues and identify solutions to complex data challenges.
- Bachelor's Degree
- Relevant Experience or Degree in: related field of study from an accredited university is required; however, relevant experience in lieu of a degree may be considered.
- Typically a minimum of 6 years
- Related professional experience including a minimum of 3 years experience in a supervisory position.
- Prefer experience with Cloud Data Lakehouse
- Master's Degree - Quantitative Analytics, Statistics, Mathematics, Data Science, or similar discipline
- Skills / Knowledge - A seasoned, experienced professional with a full understanding of area of specialization; resolves a wide range of issues in creative ways. This job is the fully qualified, career-oriented, journey-level position.
- Job Complexity - Works on problems of diverse scope where analysis of data requires evaluation of identifiable factors. Demonstrates good judgment in selecting methods and techniques for obtaining solutions. Networks with senior internal and external personnel in their own area of expertise.
- Supervision - Normally receives little instruction on day-to-day work, general instructions on new assignments.
