Data Engineering Consultant

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

Job summary

UARROW PTE. LTD. seeks a Senior Data Engineer to design, develop and optimize scalable data solutions using Big Data, cloud and AI technologies in Singapore.

You will build high-performance data pipelines, ingestion frameworks and data processing systems, collaborating with architects, data scientists and engineers to deliver production-ready solutions. The role requires strong Python/Java/Scala skills, extensive Spark/PySpark experience, and hands-on AWS data services knowledge.

Qualifications

• Degree in computer science, information technology, or engineering.
• 8+ years in Data Engineering / Big Data with large-scale processing.
• Strong programming in Python, Java and/or Scala.
• Hands-on with Spark/PySpark, SQL, Hadoop and Hive.
• Experience with AWS and data warehousing / lake tech.
• Familiarity with Kafka, Airflow and CI/CD practices.

Responsibilities

• Design, develop and optimize scalable data pipelines (batch/real-time).
• Develop ETL/ELT processes for large-scale data processing.
• Build data ingestion using databases, APIs, files and streaming platforms.
• Work with AWS services: S3, Glue, EMR, Redshift, Kinesis, Lambda, DynamoDB.
• Optimize data processing using Hadoop, Hive, Spark, Kafka, Cloudera, Databricks.
• Tune SQL and Spark performance for large workloads.
• Design data models, data warehouses and data lake solutions.
• Develop CI/CD pipelines; support Docker/Kubernetes/OpenShift deployments.
• Integrate Generative AI, NLP, LLMs, RAG, and vector databases where needed.
• Collaborate with architects, data scientists and engineers from conception to production.

Skills

Python

Java/Scala

SQL

Apache Spark

ETL/ELT design

Data processing

Education

Bachelor’s degree in CS/IT/Engineering

Master’s degree

Tools

Docker

Kubernetes

OpenShift

AWS

Databricks

Snowflake

Cloudera

Hadoop

Airflow

Jenkins

Git

CI/CD

Job description

Job Description

We are looking for a highly skilled and experienced Senior Data Engineer to design, develop and optimize scalable data engineering solutions using Big Data, cloud and modern AI technologies.

The successful candidate will be responsible for developing high-performance data pipelines, data ingestion frameworks and data processing solutions, while working closely with architects, business stakeholders, data scientists and engineering teams.

Key Responsibilities

• Design, develop and maintain scalable batch and real-time data pipelines using Apache Spark/PySpark, SQL and Python.


• Develop and optimize ETL/ELT pipelines for large-scale data processing.


• Build data ingestion solutions using databases, APIs, files and streaming platforms.


• Work with AWS services including S3, Glue, EMR, Redshift, Kinesis, Lambda and DynamoDB.


• Develop and optimize data processing solutions using Hadoop, Hive, Spark, Kafka, Cloudera and Databricks.


• Perform SQL and Spark performance tuning and optimize large-scale data processing workloads.


• Design and implement data models, data warehouses and data lake solutions.


• Develop CI/CD pipelines and support containerized deployments using Docker, Kubernetes and OpenShift.


• Integrate Generative AI and NLP capabilities into enterprise data applications where required.


• Develop solutions using LLM frameworks, RAG, vector databases and AI APIs.


• Collaborate with solution architects, data scientists, software engineers and business stakeholders to deliver production-ready solutions.


• Participate in system design, development, testing, deployment and production support.

Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering or a related field.


• Minimum 8 years of relevant experience in Data Engineering / Big Data, with strong experience in large-scale data processing.


• Strong programming experience in Python, Java and/or Scala.


• Strong hands-on experience with Apache Spark/PySpark, SQL, Hadoop and Hive.


• Experience with cloud platforms, particularly AWS.


• Experience with data warehouses, relational databases and data lake technologies.


• Experience with Kafka, Airflow, Jenkins, Git and CI/CD practices.


• Experience with Docker, Kubernetes or OpenShift is advantageous.


• Knowledge of Databricks, Snowflake and Cloudera is advantageous.


• Exposure to Generative AI, LLMs, RAG, LangChain/LangGraph and vector databases is an advantage.


• Strong analytical, problem-solving and communication skills.

Technical Skills

Python, Java, Scala, PySpark, Apache Spark, SQL, Hadoop, Hive, Kafka, Databricks, Cloudera, AWS, S3, Glue, EMR, Redshift, Kinesis, Lambda, Airflow, Jenkins, Docker, Kubernetes, OpenShift, Snowflake, MongoDB, Oracle, PostgreSQL and Generative AI technologies.