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First VP, Senior Data Engineer, Group Technology & Ops

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design metadata-driven ingestion frameworks for batch, CDC, streaming, APIs and files

  • Build Bronze, Silver and Gold layers using Lakehouse principles

  • Create business-facing data products with metadata, lineage and SLAs

  • Implement data quality controls and observability

  • Performance tune Spark jobs and distributed processing workloads

From the employer’s posting
Design metadata-driven ingestion frameworks supporting batch, CDC, streaming, APIs and files.
Build Bronze, Silver and Gold layers using Lakehouse principles.
Create business-facing data products with metadata, lineage and SLAs.
Implement data quality controls and observability.
Performance tune Spark jobs and distributed processing workloads.

What you’ll bring

All qualifications

Core experience

  • At least 15 years in technology delivery, preferably banking or financial services
  • Master's degree in computer science or a related discipline
  • Apache Spark (PySpark) and Java or Python programming
  • Advanced SQL and data modeling
  • Delta Lake/Lakehouse concepts and ETL/ELT with CDC
Qualification wording
At least 15 years of experience in technology delivery, preferably within banking or financial services
Master’s degree in computer science or a related disciplines.
Apache Spark (PySpark) Java, Python
Advanced SQL Data Modeling
Delta Lake/Lakehouse concepts ETL/ELT and CDC
Education & alternatives
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

About United Overseas Bank

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 the employer’s words · Read in context

Apply at United Overseas Bank

Posting record

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Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 20268 days ago
Recorded sightings
9
Last seen by us
Nov 13, 2026
Employer says posted
Aug 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 8

Similar jobs usually come down between day 6 and day 56.

From 13,630 similar postings that came down. Coming down is not always a hire.

United Overseas Bank is hiring

48 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • SQL
  • Delta Lake
  • Docker
  • Hadoop
  • Hive
  • Iceberg
  • Kafka
  • Kubernetes
  • MLflow
  • Spark
  • Terraform
  • Trino
  • Airflow
  • Flask
  • PySpark
  • React
  • scikit-learn
  • XGBoost
Where the posting names them
- 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 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.
- Apache Spark (PySpark) - Java, Python - Advanced SQL
- 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.
- 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 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).
- Java, Python - Advanced SQL - Data Modeling
- Data Modeling - Delta Lake/Lakehouse concepts - ETL/ELT and CDC
- 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)
- 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:
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.
- Airflow - Kubernetes - Terraform
- Implement data quality controls and observability. - Performance tune Spark jobs and distributed processing workloads. - Support DevOps, CI/CD and Infrastructure as Code practices.
Mandatory Skills - Apache Spark (PySpark) - Java, Python
- Kubernetes - Terraform - Data Products
Preferred Skills - Airflow - Kubernetes

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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.

Apply now and make a Difference

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