Senior Data & Analytics Technical Lead

re-zoo-me; Singapore; Hybrid; SGD 90,000 - 150,000; Full time

Job summary

re-zoo-me is seeking a data engineer to design, develop and support enterprise-scale data engineering solutions across banking and financial services. You will build scalable data pipelines, implement ETL processes, and optimize data platforms to ensure high data quality and performance.

The role covers modern data estate activities, including data migration, batch processing, and CI/CD for data deployments, with opportunities to collaborate across business and infrastructure teams.

Qualifications

• Degree in Computer Science, IT, Data Engineering, or related field.
• Strong hands-on data engineering, ETL, warehousing, and Big Data experience.
• Proficient in Python, PySpark, SQL, and Hive/HQL.
• Experience with Hadoop, Spark, and enterprise data platforms.
• Experience with Talend, DataStage, and/or Informatica.
• Experience with Teradata, Oracle, or SQL Server.
• Unix/Linux and shell scripting knowledge.
• CI/CD experience using Git and Jenkins.
• Strong data modelling, data quality, and pipeline optimization.
• Banking/financial services exposure is a plus.

Responsibilities

• Design, develop, and optimize scalable data pipelines and ETL processes.
• Develop and maintain data processing solutions using Python, PySpark, SQL, Hive, and Spark.
• Work with Big Data platforms like Hadoop HDFS, Hive, and cloud storage.
• Perform data extraction, transformation, and loading from multiple sources.
• Design and implement data migration and modernization with DataStage, Talend, Informatica, and Hadoop.
• Develop and optimize batch processing and scheduling with Autosys and Control-M.
• Conduct data profiling, data quality checks, and performance tuning.
• Support data warehouse and dimensional modelling activities.
• Implement CI/CD processes for data pipeline deployments.
• Collaborate with business, application, and infrastructure teams.
• Provide technical leadership and production support for enterprise data platforms.

Skills

Python

PySpark

SQL

Hive/HQL

Hadoop

Spark

ETL

Data Warehousing

CI/CD

Git

Jenkins

Unix/Linux

Shell scripting

Data modelling

Data quality

Education

Bachelor's degree in Computer Science or related

Tools

Talend

DataStage

Informatica

Snowflake

Cloudera

Autosys

Control-M

Hadoop ecosystem tools

Job description

Job Summary

We are looking for a data engineer to design, develop, and support enterprise-scale data engineering solutions. The role will focus on data pipelines, ETL processing, big data platforms, data migration, data quality, and optimization across banking and financial services environments.

Key Responsibilities

• Design, develop, and optimize scalable data pipelines and ETL processes.
• Develop and maintain data processing solutions using Python, PySpark, SQL, Hive, and Spark.
• Work with Big Data platforms, including Hadoop HDFS, Hive, and cloud/object storage environments.
• Perform data extraction, transformation, and loading from multiple source systems.
• Design and implement data migration and modernization solutions involving DataStage, Talend, Informatica, and Hadoop.
• Develop and optimize batch processing and scheduling workflows using Autosys and Control-M.
• Perform data profiling, data quality checks, and performance optimization.
• Support data warehouse and dimensional data modelling activities.
• Implement CI/CD processes for data pipeline deployments.
• Work with business, application, and infrastructure teams to deliver data solutions.
• Provide technical leadership and production support for enterprise data platforms.

Requirements

• Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
• Strong experience in data engineering, ETL, data warehousing, and Big Data technologies.
• Strong hands-on experience in Python, PySpark, SQL, and Hive/HQL.
• Experience with Hadoop, Spark, and enterprise data platforms.
• Experience with Talend, DataStage, and/or Informatica.
• Experience with Teradata, Oracle, or SQL Server.
• Experience with Unix/Linux and shell scripting.
• Experience with CI/CD tools such as Git and Jenkins.
• Strong understanding of data modelling, data quality, and data pipeline optimization.
• Banking or financial services experience will be an advantage.

Preferred Skills

• Experience with Snowflake and Cloudera.
• Experience with Autosys, Control-M, or similar scheduling tools.
• Experience in large-scale data migration and technology modernization.
• Strong stakeholder management and technical leadership skills.