Senior Data Engineer – Banking/Financial

UARROW PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

UARROW PTE. LTD. in Singapore seeks a seasoned Data Engineering Leader to design and implement large-scale data pipelines and ETL solutions within Banking/Financial Services.

You will leverage Python, PySpark, SQL, Hadoop HDFS, Spark, Hive and Teradata to build scalable data platforms, drive data quality, governance and performance tuning, and mentor a team of data engineers through delivery governance and production support.

Qualifications

• 15+ years of hands-on experience in data engineering and data warehousing.
• Strong ETL and enterprise data platform experience.

Responsibilities

• Design and implement large-scale data pipelines and ETL frameworks.
• Lead data engineering teams with code reviews and production support.
• Migrate and modernize legacy banking data platforms.

Skills

Data engineering

Data warehousing

ETL

Data platforms

Stakeholder management

Tools

Python

PySpark

SQL

Hadoop HDFS

Spark

Hive

Teradata

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.