Senior Data Engineer

N/A

Nộp Đơn Ứng Tuyển

Địa điểm

Hà Nội

Ngày cập nhật
26/03/2026
Ngành nghề
CNTT - Phần mềm, Ngân hàng
Hình thức
Nhân viên chính thức
Cấp bậc
Nhân viên

Lương
Thỏa thuận
Kinh nghiệm
Không yêu cầu kinh nghiệm
Số lượng
1
Hết hạn nộp
26/04/2026

Phúc lợi

Chế độ bảo hiểm
Du Lịch
Chế độ thưởng
Chăm sóc sức khỏe
Đào tạo
Tăng lương
Laptop
Phụ cấp
Du lịch nước ngoài
Đồng phục
Công tác phí
Phụ cấp thâm niên
Nghỉ phép năm
CLB thể thao

Mô tả 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 Công Việc

• 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