At a Glance
- Tasks: Build and optimise data pipelines for global money management.
- Company: Join Wise, a leading tech company revolutionising international payments.
- Benefits: Enjoy competitive pay, flexible work options, and growth opportunities.
- Other info: Collaborative team environment with a focus on career development.
- Why this job: Make a real impact on how the world manages money with innovative tech.
- Qualifications: Experience in Python, SQL, and data modelling required.
The predicted salary is between 59400 - 72600 £ per year.
Wise is a global technology company, building the best way to move and manage the world’s money. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money.
Skills, with evidence:
- Airflow / orchestration: Proven track record building, scheduling, and monitoring production pipelines using modern workflow orchestrators such as Apache Airflow.
- Domain Data Modelling: Mapping complex transactional events into coherent, business-accurate data models that define how customer onboarding funnels, verification triggers, and conversion metrics are tracked.
- Python: Solid software engineering skills in Python with the ability to write clean, maintainable code, navigate complex algorithms, and optimize data-intensive tasks for performance and computational efficiency.
- SQL: Extensive experience designing normalized and dimensional data models, paired with strong proficiency in crafting, debugging, and tuning complex SQL queries over large-scale datasets.
- Observability & Auditability: Ensuring that every onboarding flow and FinCrime control is measurable, auditable, and transparent out-of-the-box for regulatory compliance and product health monitoring.
- Improve Performance & Scale: Optimise data-intensive workflows and queries, resolving latency bottlenecks and ensuring data consistency across personal, business, and platform onboarding spaces.
- Streaming Data Ingestion & Pipelines: Designing and maintaining robust ETL/ELT pipelines that ingest high-volume, event-driven data from verification services and transform it into reliable analytical stores.
- Set Data Engineering Standards: Partner with engineering, analytics, and compliance to define shared data contracts, pipeline monitoring best practices, and automated testing frameworks across the squad.
- Familiarity with distributed compute and storage platforms: (e.g., Kafka, Spark, Snowflake, or Presto/Trino).
- Hands-on experience with modern data transformation tools: like dbt.
- Machine learning: While customer-facing systems fire dozens of raw operational events per verification flow, our analytics and machine learning teams require structured, clean, and reliable metrics to steer the business.
Senior Data Engineer I - Global KYC & Onboarding in London employer: D8 LooP
Wise is an exceptional employer that fosters a dynamic and innovative work culture, where employees are empowered to make a real impact on the global financial landscape. With a strong focus on employee growth and development, team members have access to cutting-edge technology and opportunities to enhance their skills in a collaborative environment. Located in a vibrant city, Wise offers unique advantages such as flexible working arrangements and a commitment to work-life balance, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer I - Global KYC & Onboarding in London
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We think you need these skills to ace Senior Data Engineer I - Global KYC & Onboarding in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at D8 LooP
✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
