Senior Data Engineer Banking/Financial

uarrow pte. ltd.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

uarrow pte. ltd. in Singapore seeks a hands-on Senior Data Engineer to architect and scale enterprise data platforms for Banking/Financial services.

You will lead data pipelines using Python, PySpark, SQL, Hadoop HDFS, Spark, Hive and Teradata, and drive migration and optimisation of ETL platforms (Talend/DataStage/Informatica).

You will mentor teams, enforce data quality, and collaborate with Technology, Analytics and Compliance stakeholders on regulatory data initiatives.

Qualifications

• 15+ years hands-on experience in data engineering and enterprise data platforms.
• Strong expertise in Python, PySpark, SQL, Hadoop HDFS, Spark, Hive, Teradata.
• Proven ability to design large-scale ETL pipelines and batch processing.
• Experience with migration/optimisation of ETL platforms (Talend/DataStage/Informatica).
• Leadership of large data engineering teams and production support.
• Experience with data governance topics and data quality, lineage.

Responsibilities

• Lead data engineering teams, review designs and troubleshoot issues.
• Oversee delivery governance and production support.
• Design data architecture frameworks and CI/CD pipelines.
• Collaborate with banking technology teams and stakeholders.

Skills

Python

PySpark

SQL

Hadoop HDFS

Spark

Hive

Teradata

Tools

Talend

DataStage

Informatica

Autosys

Control-M

Jenkins

Git

Job description

15+ years of hands-on experience in Data Engineering, Data Warehousing, ETL and enterprise data platforms, preferably within Banking/Financial Services.

Strong hands-on expertise in Python, PySpark, SQL, Hadoop HDFS, Spark, Hive and Teradata; candidates without these core technologies will not be considered.

Proven experience designing and implementing large-scale data pipelines, ETL frameworks, data integration and batch processing solutions.

Extensive experience with at least one enterprise ETL platform such as Talend, DataStage or Informatica, including migration and optimisation.

Strong experience in Teradata-to-Hadoop/Data Lake migration, legacy platform modernisation, technology refresh and application decommissioning.

Experience working on enterprise Banking data platforms, preferably with Retail Banking, Cards, AML, Fraud, Regulatory Reporting or Data Warehouse environments.

Hands-on experience with data modelling, data profiling, data quality, data lineage, data transformation and large-volume structured/unstructured datasets.

Proven technical leadership of large data engineering teams, including solution design, code/design reviews, technical troubleshooting, delivery governance and production support.

Strong experience designing data architecture/frameworks, CI/CD pipelines, orchestration and batch processing using tools such as Autosys, Control-M, Jenkins and Git.

Experience with enterprise data migration, performance tuning, job optimisation, capacity planning and production/BAU support in high-volume banking environments.

Experience delivering regulatory or risk-data initiatives, such as AML, Fraud, MAS regulatory requirements, BCBS239, data quality or critical data element lineage.

Strong stakeholder management with Banking technology teams, Business Analysts, Infrastructure teams, Data Management teams and senior client stakeholders, with ownership of technical solution delivery.