Data Engineer - MSB - KCN - 3I142

• Platform Construction: Build, operate, and define the strategic architecture for the Big Data and Lakehouse platform using Delta Lake, Apache Iceberg, and Medallion architectures (Bronze/Silver/Gold).
• Infrastructure Management: Manage, monitor, and scale data infrastructure across On-Prem and OpenShift/Kubernetes container platforms.
• Data Integration & Pipelines: Design, develop, and optimize robust batch and real-time data pipelines using Airflow, Kafka Streaming, and low-latency CDC models.
• Advanced Processing (PySpark/Spark): Develop, tune, and maximize the performance of processing jobs using Apache Spark and PySpark at the cluster level for massive datasets.
• Performance & Cost Optimization: Continuous tuning of system performance (Spark, Presto,…) and cloud resource utilization to reduce overall operational costs.
• Data Governance & Security: Enforce data quality, security policies, lineage, and catalogs (OpenMetadata) in compliance with strict Banking & Finance regulations.
• 24/7 Operations: Establish real-time monitoring/alerting dashboards, handle incident management, lead root-cause analysis, and ensure system availability and SLAs.
• Technical Leadership: Lead, mentor, review code, and set engineering standards/best practices for the team of Data, Platform, and Cloud Engineers.
• Cross-Functional Collaboration: Partner closely with BA, BI, Data Science, and Source IT teams to evaluate integration feasibility and deliver data solutions.

• Education: Bachelor’s degree or higher in IT, Computer Science, Data Science, Management Information Systems, or related fields.
• Core Experience: Minimum 4+ years of professional experience in Data Engineering, Big Data, or Data Platform roles, including senior or technical leadership capacity.
• Technical Ecosystem (Must-Have): Deep expertise in Apache Spark, PySpark, Presto, ApacheKafka, Storage, and Airflow orchestration.
• K8s & DevOps Expertise: Strong hands-on experience in Kubernetes/OpenShift administration, containerizing big data workloads, configuring K8s networking/storage, and
building automated CI/CD pipelines (GitLab CI, Jenkins, or ArgoCD) for data applications.
• Architecture & Coding: Strong command of Lakehouse architecture, open table formats (Delta/Iceberg), complex SQL optimization, and Python / Scala / Java.
• Cloud & Containers: Proven practical experience with AWS cloud services and OpenShift or Kubernetes container environments.
• Production Operations: Experience operating 24/7 production data systems, handling pipelines failure, data replay, backfilling, and ensuring idempotency.
• Preferred Tools: Familiarity with Git, CI/CD, Infrastructure as Code (Terraform), OpenMetadata, IBM Cloud Pak for Data (CP4D), IBM CDC, watsonx, or Databricks.
• Certifications (Plus): Professional certifications in Data Engineering (AWS/GCP, Databricks, Cloudera, IBM) or Kubernetes (CKA/CKAD) are a major advantage.
• Language: Proficient in English, especially in reading and understanding complex technical documentation (TOEIC 550+ equivalent).
• Soft Skills & Attributes:o Strong systems thinking, change management capability, and a passion for driving a
data-centric culture.
o Calm under pressure, proactive, meticulous, and highly responsible for 24/7 production environments.
o Excellent communication skills to mentor team members and collaborate effectively in complex cross-functional setups.
• Industry Background: Prior experience working in Banking, FinTech, or large financial institutions is a significant asset.

QUYỀN LỢI KHI GIA NHẬP MSB

1. Attractive Compensation and Bonuses:
• Competitive salary aligned with market standards and commensurate with capabilities, to be negotiated upon successful completion of the interview process.
• Year-end performance bonus ranging from 2 to 5 months of the average annual salary, depending on performance evaluation results.

2. Comprehensive Benefits Policy:
• Statutory insurance in accordance with the law and additional private health insurance for employees.
• Diverse benefits including flexible working hours, company trips, birthday leave, and more.
• Preferential loan programs available for employees.

3. Training and Career Advancement:
• Structured and in-depth training programs oriented toward transformation (Re-skill, Up-skill, New-skill), tailored to each job group.
• Close guidance and mentorship from leaders, direct managers, and industry experts.
• Management development programs for high-potential employees, preparing them for future leadership roles.
• Priority given to internal candidates for management positions, creating strong career advancement opportunities.

4. Professional Working Environment and Dynamic Corporate Culture:
• Friendly and open environment that emphasizes responsibility, collaboration, and mutual support.
• Dynamic and creative workplace that encourages innovation and continuous learning.
• Respect for diversity, with a strong focus on teamwork and effective collaboration.
• Engaging cultural, sports, and recreational activities that foster a connected and enjoyable workplace.