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- Tasks: Join our Data Engineering team to build and optimise our data platform using modern tools.
- Company: Visa, a leading global payments technology company with a commitment to innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact by enabling better decision-making through powerful data analytics.
- Qualifications: Experience in Data Modelling, ETL projects, and proficiency in Python or Java.
- Other info: Collaborative environment with a focus on best practices and data governance.
The predicted salary is between 36000 - 60000 £ per year.
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.
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:
- 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:
- 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).
Staff Data Engineer in London employer: Visa
Contact Detail:
Visa Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Data Engineer in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works in data engineering. Building relationships can open doors that job applications alone can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving Snowflake, dbt, or Airflow. This gives potential employers a tangible sense of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your SQL and data modelling skills. Be ready to discuss your past projects and how you've optimised data processes. Remember, confidence is key!
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing passionate candidates who are eager to join our team.
We think you need these skills to ace Staff Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Staff Data Engineer role. Highlight your experience with data modelling, ETL projects, and any relevant tools like Snowflake or dbt. We want to see how you can contribute to our data platform!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our mission at StudySmarter. Don’t forget to mention any experience with cloud technologies and data governance.
Showcase Your Projects: If you've worked on any cool data projects, make sure to include them in your application. Whether it's optimising a data warehouse or implementing best practices, we love seeing real-world examples of your work and how you’ve made an impact.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Visa
✨Know Your Tools Inside Out
Make sure you’re well-versed in the tools mentioned in the job description, like Snowflake, dbt, and Airflow. Brush up on your knowledge of data modelling, ETL processes, and any relevant programming languages like Python or Java. Being able to discuss your hands-on experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've optimised data warehouses or reduced costs in previous roles. Think about specific challenges you faced and how you tackled them. This will demonstrate your proactive approach to identifying issues and improving processes, which is key for this role.
✨Understand Data Governance
Familiarise yourself with data governance best practices and be ready to discuss how you’ve implemented these in past projects. Highlight your experience in ensuring data quality and compliance, especially if you’ve worked in regulated environments. This will show that you can contribute to prioritising data governance issues effectively.
✨Be Ready for Technical Questions
Expect technical questions related to data warehousing concepts, SQL queries, and possibly even coding challenges. Practice common interview questions and scenarios that might come up. This will help you feel more confident and prepared to showcase your technical expertise during the interview.
