Data Engineer I
Role details
Job location
Tech stack
Job description
The Data Track exists to provide high-quality, trustworthy payments data that powers business decisions and enables great experiences for travelers and partners, aligning Fintech foundations with robust governance and reliable delivery across reporting and analytics consumers.
Mission: Provide high-quality payments data that powers impactful decisions and enables exceptional experiences for travelers and partners.
Vision: Achieve "Flawless Payments Analysis and Reporting" across Fintech by ensuring stakeholders can trust and act on data with confidence.
Scope: Govern, acquire, cleanse, enrich, store, and distribute comprehensive, reliable transactional data; additionally manage card data and ensure PCI DSS compliance.
Core capabilities: Operate and evolve the data platform (consumption, transformation, enrichment), deliver reports/dashboards/alerts, improve data quality and lineage, and support analytics and machine learning use cases.
The Junior Data Engineer is responsible for supporting development and delivery of end-to-end data solutions. The incumbent supports solution envisaging and technical designs, and drives hands-on implementation. Supports the influencing, differentiation, and guidance to business and technology strategies, as they relate to data, through constant cross-functional interaction., * Drive efficiency and resilience by mapping data flows between systems and workflows across the company
- Ensure standardisation by following design patterns in line with global and local data governance requirements
- Support real-time internal and customer-facing actions by developing real-time event-based streaming data pipelines
- Enable rapid data-driven business decisions by supporting development of efficient and scalable data ingestion solutions
- Drive high-value data by connecting different disparate datasets from different systems
- Monitor and follow relevant SLIs and SLOs
- Handle, mitigate and learn from incidents in a manner that improves the overall system health
- Ensure ongoing resilience of data processes by monitoring system performance and acting proactively identifying bottlenecks, potential risks, and failure points that might degrade overall quality
- Write readable and reusable code by applying standard patterns and using standard libraries
- Continuously evolve own craft by keeping up to date with the latest developments in data engineering and related technologies, and upskilling on these as needed.
Requirements
- Bachelor's or Master's degree in Computer Science or related field
- 1-3 years of relevant job experience
- Entry level exposure to a data engineering or related field using server side programming languages, preferably Scala, Java, Python, or Perl
- Entry level exposure to building data pipelines and transformations at scale, with technologies such as Hadoop, Cassandra, Kafka, Spark, HBase, MySQL
- Basic knowledge of data modeling methods based on best practices, e.g. TOGAF
- Basic knowledge of data quality requirements and implementation methodologies
- Excellent English communication skills, both written and verbal.