Senior Data & Analytics Technical Lead

JEET ANALYTICS PTE. LTD.; Singapore; On-site; SGD 100,000 - 140,000; Full time

Job summary

JEET ANALYTICS PTE. LTD.

in Singapore is seeking a data engineer to design, develop, and support enterprise-scale data engineering solutions focused on pipelines, ETL, big data platforms, data migration, and quality across banking and financial services environments. The role involves building scalable data pipelines, implementing data migration strategies, and collaborating with business, application, and infrastructure teams to deliver robust data solutions.

Qualifications

• Degree in Computer Science, IT, Data Engineering or related discipline.
• Strong experience in data engineering, ETL, data warehousing and Big Data tech.
• Hands-on with Python, PySpark, SQL and Hive/HQL.
• Experience with Hadoop, Spark and enterprise data platforms.

Responsibilities

• Design, develop and optimize scalable data pipelines and ETL processes.
• Develop data processing solutions using Python, PySpark, SQL and Hive.
• Work with 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 using DataStage, Talend, Informatica and Hadoop.
• Develop and optimize batch processing and scheduling workflows (Autosys/Control-M).
• Perform data profiling, quality checks and data modeling support for warehousing.

Skills

Python

PySpark

SQL

Hadoop

Data Warehousing

ETL

CI/CD

Education

Bachelor's degree in Computer Science/IT/Data Engineering

Tools

Talend

DataStage

Informatica

Teradata

Oracle

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 optimisation.
• 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 optimisation.
• 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.