Senior Data Engineer — AI & Big Data Pipelines

UARROW PTE. LTD.; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

UARROW PTE. LTD. is seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines using Spark, SQL, Python and cloud services. You will work across data ingestion, processing, warehousing and data lake technologies to deliver production-grade solutions.

The role emphasizes collaboration with architects, data scientists and engineers, with a focus on performance tuning, CI/CD, and containerized deployments in AWS environments.

Qualifications

• 8+ years of experience in Data Engineering / Big Data.
• Strong Python, Java or Scala programming skills.
• Deep experience with Spark/PySpark, SQL, Hadoop and Hive.
• Hands-on AWS cloud experience.
• Experience with data warehouses, data lakes and relational databases.
• Familiarity with Kafka, Airflow, Jenkins, Git and CI/CD practices.
• Knowledge of Databricks, Snowflake or Cloudera is advantageous.

Responsibilities

• Design and maintain scalable batch and real-time data pipelines.
• Develop ETL/ELT workflows for large-scale datasets.
• Create data ingestion solutions using databases, APIs, files and streaming platforms.
• Collaborate with architects, data scientists and engineers to deliver production-ready solutions.
• Implement CI/CD pipelines and containerized deployments using Docker, Kubernetes and OpenShift.
• Integrate Generative AI capabilities into enterprise data applications where required.
• Participate in system design, development, testing, deployment and production support.

Skills

Python

Java

Scala

Spark

SQL

Hadoop

Hive

Kafka

Airflow

Jenkins

Git

Docker

Kubernetes

OpenShift

Databricks

Snowflake

Cloudera

Generative AI

LLMs

LangChain

Education

Bachelor’s or Master’s in CS/IT/Engineering

Tools

AWS

S3

Glue

EMR

Redshift

Kinesis

Lambda

Docker

Kubernetes

OpenShift

Databricks

Snowflake

Job description

UARROW PTE. LTD. is seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines using Spark, SQL, Python and cloud services. You will work across data ingestion, processing, warehousing and data lake technologies to deliver production-grade solutions.

The role emphasizes collaboration with architects, data scientists and engineers, with a focus on performance tuning, CI/CD, and containerized deployments in AWS environments.