Senior Data Engineer

Mentor junior and mid- level data engineers, conduct design reviews, and leverage DataOps best practices (CI/CD, automated testing, observability)
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
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
Optimize pipelines for performance, cost- efficiency, reliability, and scalability on Google Cloud Platform (GCP)
Build high- throughput, low- latency real- time and batch data pipelines to power behavioral analytics, next- best- action recommendations, and seamless customer experiences
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
Partner closely with mobile app teams, data scientists, and business stakeholders to translate digital banking requirements into production- grade data products

Solid experience (typically 5+ years equivalent) in data engineering using Python, SQL, Spark / PySpark/
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
Proven hands- on experience with Google Cloud Platform (GCP), particularly BigQuery as a core data warehouse/lakehouse solution
Practical experience with real- time streaming technologies (Spark Streaming, Flink, Kafka Streams) and workflow orchestration (Airflow)
Solid understanding of digital banking data domains (T24 data, mobile transactions, banking products, app events, customer behavioral, corporate banking flows)
Bachelor’s Degree in Computer Science, Engineering, or a related field
Familiarity with data governance, lineage practices, and compliance requirements in a regulated banking environment
Proficiency in dbt for data transformations, Python/PySpark development, and modern data warehouse/lakehouse approaches
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)
Strong background in building and operating big data pipelines, including real- time/near- real- time processing with Spark, Spark Streaming, or equivalent frameworks
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)

Annual leave
Training
Allowances
Laptop
Insurance benefits
Healthcare
Travel
Salary increase
Bonus policy
Uniform

Cập nhật gần nhất lúc: 2026-04-04 01:25:03