Director, Data Engineering
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Key skills for this role
Role Overview
The Director, Data Engineering leads the design, development, and deployment of scalable and secure data pipelines, platforms, and ML/AI infrastructure, leveraging cloud-native technologies and big data frameworks. This role oversees the integration of structured and unstructured data sources to support advanced analytics, machine learning, and AI initiatives, and champions new tools and technologies to improve productivity, scalability, and effectiveness of data engineering efforts. The Director establishes and enforces data engineering best practices, technical standards, governance, and quality standards, ensuring continuous improvement and technical excellence, while ensuring data security, privacy, compliance, system performance, scalability, and availability across all data engineering projects and platforms. 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.
Key Skills for This Role
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Qualifications
- Basic Qualifications:
- 10+ years of relevant work experience with a Bachelor’s Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience.
- Preferred Qualifications:
- 12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD
- 10+ years of relevant work experience and a Bachelor's degree, OR 13+ years of relevant work experience.
- Experience in leading large-scale data engineering teams and projects in a complex enterprise environment.
- Experience in data architecture, ETL/ELT pipelines, data warehousing, and real-time data processing.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Kafka, Hadoop).
- Experience in data modeling, data governance, and data quality frameworks.
- Experience delivering high-impact data solutions that drive business outcomes.
- Experience working with Data and AI, designing, and building ML infrastructure to train or serve models.
- Experience with open-source data engineering tools or communities.
- Experience in financial services, payments, or a highly regulated industry.
- Experience in mentoring and developing talent within engineering teams.
- Masters, PhD in Computer Science or related technical discipline.
- Experience in working on large open-source projects, preferably in the ML infrastructure domain like TensorFlow, Ray, JAX, PyTorch, Horovod.
- Experience in contributions to open-source data engineering tools or communities.
- Experience in driving operational excellence and standard methodologies in an engineering environment.
- Experience in working with Data and AI, designing, and building ML infrastructure to train or serve models.
- Visa is an EEO Employer
- Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
About Visa
Visa is a global payments technology company that connects consumers, businesses, banks, and governments in over 200 countries through its electronic payment network, VisaNet.
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