Mô tả công việc
Tóm tắt công việc
Collaborate with Agile product teams (mobile, digital banking, corporate banking, and customer insight) to design, develop, test, implement, and support full-stack data solutions that directly impact millions of mobile banking users
Design and evolve our enterprise Data Platform with Data Vault 2.0 as the foundational modeling methodology while delivering high-quality, trusted data layers in Google Cloud
Build high-throughput, low-latency real-time and batch data pipelines to power behavioral analytics, next-best-action recommendations, and seamless customer experiences
Create scalable ingestion, transformation, quality enforcement, and serving layers that feed our Next-Gen Mobile Banking App and other Digital Banking platform products
Ensure enterprise-grade data quality, governance, lineage, security, and compliance in a highly regulated environment
Optimize pipelines for performance, cost-efficiency, reliability, and scalability on Google Cloud Platform (GCP)
Mentor junior and mid-level data engineers, conduct design reviews, and leverage DataOps best practices (CI/CD, automated testing, observability)
Partner closely with mobile app teams,
data scientists, and business stakeholders to translate digital banking requirements into production-grade data products
Yêu cầu
Bachelor's Degree in Computer Science, Engineering, or a related field
Solid experience (typically 5+ years equivalent) in data engineering using Python, SQL, Spark / PySpark/
Solid understanding of digital banking data domains (T24 data, mobile transactions, banking products, app events, customer behavioral, corporate banking flows)
Proven hands-on experience with Google Cloud Platform (GCP), particularly BigQuery as a core data warehouse/lakehouse solution
Strong background in building and operating big data pipelines, including real-time/near-real-time processing with Spark, Spark Streaming, or equivalent frameworks
Practical experience with real-time streaming technologies (Spark Streaming, Flink, Kafka Streams) and workflow orchestration (Airflow)
Proficiency in dbt for data transformations, Python/PySpark development, and modern data warehouse/lakehouse approaches
Expertise in scalable data modeling - Data Vault 2.0 strongly preferred (or demonstrated success delivering agile, auditable enterprise data models such as medallion or lakehouse patterns)
Familiarity with data governance, lineage practices, and compliance requirements in a regulated banking environment
Experience designing, developing, and optimizing RESTful APIs and/or GraphQL APIs (including schema design, performance tuning, versioning, security, rate limiting, and integration with mobile/web frontends or microservices)
Experience leveraging AI copilots and hands-on familiarity with AI agents (e.g., GitHub Copilot, Claude Code, OpenClaw, ...) to accelerate development, code review, and pipeline automation
Thông tin khác
Python
MS SQL
Apache Spark
Apache Kafka
GraphQL
GCP
RESTful API
T24
Apache Airflow
Apache Flink
PySpark
Google BigQuery
Claude
GitHub Copilot
OpenClaw
Thông tin chung
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Hạn nộp: 02/06/2026