Senior Manager, Data Engineering

Visa•Austin, TX

1d•$162,500 - $260,400•Hybrid

About The Position

The Senior Manager, Data Engineering, leads teams in designing, building, and overseeing the deployment and operation of technology architecture, solutions, and software to capture, manage, store, and utilize structured and unstructured data from internal and external sources. This role is 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. The Senior Manager acts as a leader for engineering teams, removing blockers, enabling productivity, and fostering an inclusive, high-performance culture. The role also involves coaching and developing engineers to adapt to evolving tools, frameworks, and AI-driven workflows, and partnering closely with product managers, QA, risk, compliance, and security functions to deliver safe, transparent, and customer-centric solutions. All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.

Requirements

8 or more years of relevant work experience with a Bachelor Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD.
Experience in leading teams in the design, development, and deployment of large-scale data engineering solutions.
Experience with big data technologies such as Hadoop, Spark, 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 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.

Nice To Haves

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD.
Experience with cloud platforms and services (e.g., AWS, Azure, GCP) for data engineering solutions.
Experience with machine learning and AI-powered data solutions.
Experience in developing large-scale, enterprise-class distributed systems of high availability and low latency.
Experience in leading cross-functional teams in a matrixed organization.

Responsibilities

Lead the design, development, and deployment of scalable data engineering solutions and big data systems.
Oversee the creation and maintenance of data pipelines, ensuring data quality, integrity, and consistency across multiple sources and platforms.
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.