Wise · api.smartrecruiters.com · checked today
Senior Data Engineer I - Global KYC & Onboarding
Skills, with evidence
- Airflow / orchestration
Pipeline & Workflow Orchestration: Proven track record building, scheduling, and monitoring production pipelines using modern workflow orchestrators such as Apache Airflow.
must have - Data modelling
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.
must have - Python
Strong Python Fundamentals: 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.
must have - SQL
Advanced SQL & Data Modelling: Extensive experience designing normalized and dimensional data models, paired with strong proficiency in crafting, debugging, and tuning complex SQL queries over large-scale datasets.
must have - Failure handling
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.
- Cost & performance
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.
- Governance & security
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.
not practised here - Data quality
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.
- Schema evolution & contracts
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.
- Spark
Familiarity with distributed compute and storage platforms (e.g., Kafka, Spark, Snowflake, or Presto/Trino).
- dbt
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.
not practised here
Your plan
- SQL
drills at the Senior level
- Python
drills at the Senior level
- Modelling
drills at the Senior level
- Pipelines
drills at the Senior level
- Spark
drills at the Senior level
The full plan, drill by drill, is on the job page.
leaves in 9 dremoved the moment Wise closes it