Data Scientist, AI & Big Data Platform Engineer

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

Job summary

UNISYNC SYSTEMS PTE. LTD. in Singapore seeks a seasoned Data Engineer to design, build and optimize scalable ETL/ELT pipelines for large-volume structured and unstructured data.

You will leverage Python, PySpark, Spark SQL and Scala to process data efficiently and support batch and real-time workloads using Kafka, Kinesis, Spark Streaming, AWS Glue and Airflow. The role involves data ingestion, data lakes/warehouses design, and collaboration with teams on enterprise data platforms using

Qualifications

• Experience with large-scale enterprise data platforms and production data pipelines.
• Strong programming and SQL skills.
• Experience with cloud-based data engineering and modern data processing frameworks.

Responsibilities

• Design, develop and maintain scalable ETL/ELT data pipelines for large-volume datasets.
• Develop high-performance data processing solutions using Python, PySpark, Spark SQL and Scala.
• Build batch and real-time data pipelines using Kafka, Kinesis, Spark Streaming, AWS Glue and Airflow.
• Develop data ingestion frameworks integrating RDBMS, APIs, files, cloud storage and streaming platforms.
• Design and implement data lakes, data warehouses and cloud-based data processing platforms.
• Work with Databricks, Hadoop, Hive, Cloudera, Presto and Snowflake for large-scale data processing and analytics.

Skills

Big Data

Python

SQL

Spark

Data Modeling

Cloud Computing

ETL/ELT

DevOps

REST APIs

NLP

Education

Bachelor's or Master's in CS/IT or related

Tools

Databricks

Hadoop

Snowflake

Kafka

OpenShift

Job description

UNISYNC SYSTEMS PTE. LTD. in Singapore seeks a seasoned Data Engineer to design, build and optimize scalable ETL/ELT pipelines for large-volume structured and unstructured data.

You will leverage Python, PySpark, Spark SQL and Scala to process data efficiently and support batch and real-time workloads using Kafka, Kinesis, Spark Streaming, AWS Glue and Airflow. The role involves data ingestion, data lakes/warehouses design, and collaboration with teams on enterprise data platforms using