Director, Data Engineering
Visa is hiring a Director, Data Engineering in Bengaluru, India. Level rates it ; you can apply on Visa.
Level's read on this job
- On Level's scale, this data engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include ChatGPT, Copilot and PyTorch.
- Level classifies it as a lead role.
- Level lists 822 other open roles at Visa.
AI in this role
Lead the design and deployment of scalable data pipelines, data platforms, and ML/AI infrastructure at Visa.
About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
Job Description
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 Responsibilities:
- Lead the design, development, and deployment of scalable and secure data pipelines, platforms, and ML/AI infrastructure.
- Oversee integration of structured and unstructured data sources to support advanced analytics, machine learning, and AI initiatives.
- Evaluate, implement, and champion new tools and technologies to improve productivity, scalability, and effectiveness of data engineering efforts.
- Establish and enforce data engineering best practices, technical standards, governance, and quality standards.
- Ensure data security, privacy, compliance, system performance, scalability, and availability across all data engineering projects and platforms.
- Define, monitor, and report on key performance indicators (KPIs) to measure the success and impact of data engineering activities.
- Lead incident response, root cause analysis, and resolution for data platform issues, ensuring high availability and reliability.
- Collaborate with cross-functional teams to deliver robust data-driven business solutions and define technical roadmaps.
- Mentor, coach, and grow a high-performing team of data engineers, fostering a culture of innovation, excellence, and continuous learning.
- Partner with senior leadership to define, execute, and communicate the enterprise data strategy.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
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.
- 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.
- 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.
How we rate this
Director, Data Engineering at Visa rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical data engineer job
- $145k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where ml infrastructure was part of your work. What did you do?
- Tell me about a project where cloud native was part of your work. What did you do?
- Tell me about a project where big data was part of your work. What did you do?
- Walk me through how you've used ChatGPT in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Engineering, ML Infrastructure, Cloud Native, Big Data, and ChatGPT. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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