REGTECH INSIGHT PTE. LTD. Hiring! Full Time DATA ENGINEER in Central Region (Singapore), Earn up to SGD 9,000 - Ricebowl

Key Responsibilities

Design, develop and maintain scalable

data pipelines and data ingestion frameworks

for large-volume datasets.

Develop data transformation and processing applications using

Apache Spark, PySpark, Scala and Python

.

Build and optimize data pipelines using

Azure Databricks, Azure Data Factory, AWS EMR

and related cloud services.

Work with

Hadoop, HDFS, Hive, Snowflake, Teradata and Data Lake

environments.

Develop batch and real-time data processing solutions using

Spark Structured Streaming and Kafka

.

Perform data extraction, transformation and loading across heterogeneous source and target systems.

Develop and optimize

Spark SQL, HiveQL and SQL

queries for performance and cost efficiency.

Design data models, partitioning strategies and scalable data storage architectures.

Build and manage workflow orchestration using

Apache Airflow

.

Implement CI/CD pipelines and automated testing using tools such as

Jenkins, Docker, GitHub Actions and pytest

.

Troubleshoot data pipeline, performance and production issues and implement sustainable solutions.

Collaborate with business stakeholders, architects and technology teams to understand requirements and deliver data engineering solutions.

Ensure data quality, reliability, security and operational stability across enterprise data platforms.

Required Skills

6+ years of experience in

Data Engineering / Big Data Engineering

.

Strong hands-on experience with

Apache Spark / PySpark

.

Strong programming skills in

Python and/or Scala

.

Good experience with

Hadoop, HDFS and Hive

.

Experience developing

ETL/ELT and data ingestion pipelines

.

Strong SQL and data processing skills.

Experience with

Azure Databricks, Azure Data Factory, AWS EMR

or equivalent cloud data platforms.

Experience with

Kafka / real-time streaming

is an advantage.

Hands-on experience with

Airflow

and data pipeline orchestration.

Experience with

Snowflake, Teradata, SQL Server or other enterprise databases

.

Good understanding of

Data Lake, Delta Lake, Data Warehousing and Data Modelling

.

Experience with

Git, CI/CD, Docker and automated testing

.