Company: 1011 United Overseas Bank Ltd
About UOB
United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.
Job Description
We are seeking a hands-on Senior Data Engineer to build enterprise-scale ingestion frameworks, Lakehouse data platforms, governed data products and analytical data models using (Hive, Impala, Spark, Kafka, Iceberg, Ranger, Atlas, Nifi, Flink etc.,) The role will partner with architecture, governance, analytics and business teams to deliver trusted, reusable and AI-ready data assets.
Design metadata-driven ingestion frameworks supporting batch, CDC, streaming, APIs and files.
Develop reusable Spark/Python components, orchestration, logging, monitoring and error handling.
Build Bronze, Silver and Gold layers using Lakehouse principles.
Design conceptual, logical and physical data models.
Create business-facing data products with metadata, lineage and SLAs.
Implement data quality controls and observability.
Performance tune Spark jobs and distributed processing workloads.
Support DevOps, CI/CD and Infrastructure as Code practices.
Strong Programming skills(java, python, sql)
Build robust data ingestion and transformation frameworks using Java, Spark, Python, and shell scripting for ingesting multi model data(image, audio, video, unstructured documents) with both batch and real-time.
Strong hands on experience with Kubernetes, OpenShift, Docker, CI/CD, MLflow and observability tools.
Ability to design data architectures supporting NLP and AI‑driven analytics, including ingestion, curation, and governance of unstructured data within Data Lake, Data warehouse platforms.
Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit‑learn, XGBoost), including model deployment.
Design and develop highly scalable, Real time systems using Hadoop ecosystem components(Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink and Nifi)
Strong experience in building full agentic application with all the features(e.g mcp/tools/memory/rag)
Experienced Cloud platforms and Cloud based app deployments with observability
Strong exposure to AI-driven risk scoring, fraud investigation and explainable AI use cases in banking.
Develop full‑stack applications and internal engineering tools using Python, shell scripting, and modern web frameworks (e.g., Flask, React).
Collaborate closely with data scientists to operationalize machine learning models using Cloudera Machine Learning (CML).
Perform performance tuning and optimization of data applications on Hadoop to ensure optimal resource utilization
Job Requirements
Master's degree in computer science or a related disciplines.
At least 15 years of experience in technology delivery, preferably within banking or financial services
Mandatory Skills
Apache Spark (PySpark)
Java, Python
Advanced SQL
Data Modeling
Delta Lake/Lakehouse concepts
ETL/ELT and CDC
API integration and data engineering best practices
Preferred Skills
Airflow
Kubernetes
Terraform
Data Products
Additional Requirements
Be a Part of the UOB Family
UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.
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