Staff Data Engineer

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 You’ll be a senior contributor in our Data Engineering team, working across various projects, building out key elements of our data platform using a range of modern tools including Snowflake, dbt, and Airflow. You’ll help us minimise our cloud costs, drive best practices across all our Data Disciplines and scale and automate our data governance.

Enable VXBS (Visa Cross-Border Solutions) to Make Better Decisions, Faster

At the core of this mission sits our data platform. We’re great believers in powerful, real-time analytics and empowerment of the wider business. We optimise for simplicity and re-usability – all our data lives in one place and is made available via our data warehouse in Snowflake.

What You’ll Be Working On Working in a multi-disciplinary data engineering team, you will:

• Support the building of robust data models downstream of backend services (mostly in Snowflake) that support internal reporting, financial and regulatory use cases.
• Focus on optimisation of our Data Warehouse, spotting opportunities to reduce complexity and cost.
• Help define and manage best practices for our Data Warehouse. This may include payload design of source data, logical data modelling, implementation, metadata, and testing standards.
• Set standards and ways of working with data across VXBS, working collaboratively with others to make it happen.
• Take established best practices and standards defined by the team and apply them within other areas of the business.
• Investigate and effectively work with colleagues from other disciplines to monitor and improve data quality within the warehouse.
• Contribute to prioritisation of data governance issues.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications Degree or equivalent

You Should Apply If

• You have experience and a passion for Data Modelling, ETL projects, and Big Data as a developer or engineer
• You have good experience in Python, Java or similar languages
• You have proven experience with AWS
• SQL and data modelling is second nature to you
• You are comfortable with general Data Warehousing concepts
• You strive for improvement in your work and that of others, proactively identifying issues and opportunities
• You have experience building robust and reliable data sets requiring a high level of control
• You have proven experience with stream technologies like Kafka, Kinesis, Pulsar, etc
• You have experience working with IaC tools such as Terraform, AWS CloudFormation, or Ansible

Nice To Haves

• Any experience working within a finance function or knowledge of accounting.
• Experience working in a highly regulated environment (e.g. finance, gaming, food, health care).
• Knowledge of regulatory reporting and treasury operations in retail banking
• Have previously used dbt, Databricks, or similar tooling
• Experience working with orchestration frameworks such as Airflow/Prefect
• Design and implementation knowledge of stream processing frameworks like Flink, Spark Streaming etc.
• Used to AGILE ways of working (Kanban, Scrum)

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.