• 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

• 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

OPPORTUNITIES AND CHALLENGES:

• Opportunity to work in a professional, modern and energizing setting.
• Challenging projects, possibilities, cutting-edge technology, and problems.
• An open and dynamic working atmosphere that promotes the interchange of ideas, while also empowering you to work and create in your own style. Each employee's talent and accomplishments are valued, and outstanding employees are recognized and rewarded on a yearly basis.
• Opportunities for capacity development, as well as assistance with professional certification expenses, are available to those who work in the field (1 million - 5 million).
• Some advanced certifications will cover the full cost of studying and taking the exam.

ATTRACTIVE REWARDING POLICY AND WORK-LIFE BALANCE:

• Review salary 1-2 times/year, with the possibility of an unexpected salary rise
  based on capacity an infinite number of times per year
• Policy for 13th-Month Salary Bonus and Holiday Bonuses According to Company Regulations.
• Holiday travel mode (package 5-7 million/person), team building,…
•  Full participation in social insurance, as well as a yearly health checkup at a reputable hospital.