Description
Visa is seeking a Senior Manager, Data Engineering to lead teams in designing, building, and overseeing the development, deployment, and operation of technology architecture, solutions, and software to capture, manage, store, and utilize structured and unstructured data from internal and external sources.
The Senior Manager will be responsible for establishing processes, automations, and big data systems based on business and technical requirements, ensuring data quality, troubleshooting user issues in large distributed systems, and creating machine learning pipelines.
Key Responsibilities:
- Lead the design, development, and deployment of scalable data engineering solutions and big data systems.
- Oversee the creation and maintenance of data platform, and modernize the data platform.
- Guide teams in troubleshooting and resolving complex issues in distributed systems and data pipelines.
- Drive the adoption of automation, CI/CD, and quality engineering practices at scale.
- Coach and mentor engineering teams, fostering a culture of continuous improvement and technical excellence.
- Collaborate with cross-functional partners to ensure solutions meet business priorities, regulatory requirements, and data governance standards.
- Ensure adherence to data management principles, governance, and security protocols throughout the data lifecycle.
- Lead the implementation of advanced data protocols, reduction techniques, and aggregation approaches to validate and optimize data quality.
- Oversee the development and maintenance of technical and data documentation, and ensure best practices in code quality and review processes.
Qualifications:
- 10+ years of relevant work experience and a Bachelor's degree, OR 14+ years of relevant work experience.
- Experience in leading teams in the design, development, and deployment of large-scale data engineering solutions.
- Experience with big data technologies such as Hadoop, Hive, HBase, Spark, Trino and distributed data systems.
- Experience in building and maintaining data pipelines, ETL processes, and data quality frameworks.
- Experience with programming languages and tools such as Java, Python, SQL, and version control systems (e.g., Git).
- Experience in troubleshooting and resolving issues in complex, high-volume data environments.
- Experience in implementing data governance, security, and compliance standards.
- Experience in coaching and mentoring engineering teams.
- Experience collaborating with cross-functional teams to deliver business solutions.
- Experience in developing and maintaining technical and data documentation.