V

Visa

Runs a global network for digital payments

Director Data Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeBellevue, WA, USA

About the Job

Requirements

  • At least 10 years of relevant work experience with a bachelor's degree, or 13 or more years of relevant work experience.
  • Preferred qualification pathways include 12 or more years of work experience with a bachelor's degree, 8–10 years with an advanced degree (such as a master's, MBA, JD, or MD), or 6 or more years with a PhD.
  • Experience 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 big data technologies such as Spark, Kafka, and 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 and designing and building machine-learning infrastructure to train or serve models.
  • Experience with open-source data engineering tools or communities.
  • Hands-on development experience building real-time and streaming infrastructure and demonstrating DevOps excellence.
  • Advanced architectural experience with large-scale event-driven systems using Apache Kafka, Apache Pulsar, AWS Kinesis, or Google Cloud Pub/Sub.
  • Hands-on mastery or architectural oversight of real-time processing frameworks such as Apache Flink, Apache Spark Streaming, Kafka Streams, and Ray.
  • Deep knowledge of low-latency storage systems, column-oriented databases, and OLAP query engines such as Apache Pinot, Apache Iceberg, ClickHouse, Cassandra, and Redis.
  • Experience building multi-tenant streaming platforms with strong isolation, rate limiting, dynamic resource allocation, and zero-downtime schema evolution using Protobuf or Avro.
  • Demonstrated success implementing SLOs, SLAs, error budgets, and high-cardinality distributed tracing and monitoring systems such as Prometheus, Grafana, Datadog, or OpenTelemetry.
  • Strong problem-solving and analytics skills, and the ability to form and advocate an independent viewpoint.
  • Ability to foster a GenAI-first culture by helping engineers integrate generative AI into daily workflows and scale its business use.
  • Experience in financial services, payments, or a highly regulated industry.
  • Experience mentoring and developing talent within engineering teams.
  • A master's or PhD in Computer Science or a related technical discipline.
  • Experience working on large open-source projects, preferably ClickHouse, Redis, Flink, Kafka, or Ray.
  • Experience driving operational excellence and standard methodologies in an engineering environment.

Responsibilities

  • Lead the design, development, and deployment of scalable and secure data pipelines, platforms, and machine-learning and AI infrastructure.
  • Oversee the integration of structured and unstructured data sources to support advanced analytics, machine learning, and AI initiatives.
  • Evaluate, implement, and champion tools and technologies to improve the 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 data engineering projects and platforms.
  • Define, monitor, and report on key performance indicators to measure the success and impact of data engineering activities.
  • Lead incident response, root cause analysis, and resolution for data platform issues to ensure high availability and reliability.
  • Collaborate with cross-functional teams to deliver data-driven business solutions and define technical roadmaps.
  • Mentor, coach, and grow a high-performing team of data engineers, fostering innovation, excellence, and continuous learning.
  • Partner with senior leadership to define, execute, and communicate enterprise data strategy.

Desired Qualifications

  • Experience in working with data and AI, designing, and building machine-learning infrastructure to train or serve models.
  • Experience contributing to open-source data engineering tools or communities.

About the Company

Visa

Runs a global network for digital payments

Visa runs a global payment network that connects banks, merchants and consumers so card purchases and money transfers move between financial institutions. Its VisaNet system handles authorization, clearing and settlement, linking the bank behind a buyer's card with the bank that accepts a merchant's payment. The company earns fees from payment activity, transaction processing and international transactions, and sells fraud prevention tools, payment software and consulting services to businesses. Banks and other partners issue Visa branded cards and use its technology to build their own payment products. Visa traces its roots to a Bank of America card program launched in 1958 and is headquartered in San Francisco.

Company size
10,001+
Company stage
N/A
Total funding
$24.2M
Headquarters
San Francisco, CA
Founded
1958

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