Data Engineering Consultant at JEET ANALYTICS PTE. LTD.

JEET ANALYTICS PTE. LTD.; Singapore; Hybrid; SGD 180,000 - 240,000; Full time

Job summary

JEET ANALYTICS PTE. LTD. in Singapore seeks an experienced Senior Data Engineer to design, build and optimize scalable data pipelines using Spark, PySpark, SQL and Python.

You will work with AWS services to ingest, process and store data, and will implement data lake and warehouse solutions while leveraging CI/CD pipelines with Docker and Kubernetes. The role requires 8+ years in Data Engineering, strong programming with Python/Java/Scala, and hands-on experience with Hadoop, Hive, Kafka and

Qualifications

• Bachelor’s or Master’s degree in CS/IT/Engineering or related field.
• 8+ years in Data Engineering/Big Data with large-scale processing.
• Strong programming in Python, Java and/or Scala.
• Experience with Spark/PySpark, SQL, Hadoop and Hive.
• Cloud experience, preferably AWS.

Responsibilities

• Design, develop and maintain scalable batch and real-time data pipelines.
• Build ETL/ELT pipelines for large-scale data processing.
• Create data ingestion solutions from databases, APIs, files and streaming.
• Work with AWS services including S3, Glue, EMR, Redshift, Kinesis, Lambda and DynamoDB.
• Develop data models, warehouses and data lake solutions.
• Implement CI/CD pipelines with Docker, Kubernetes and OpenShift.
• Integrate Generative AI, LLMs, RAG into enterprise data apps.
• Collaborate with architects, data scientists and stakeholders.

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

Generative AI

Education

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering or a related field

Tools

Databricks

Snowflake

Cloudera

Airflow

Jenkins

Git

Docker

Kubernetes

OpenShift

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.

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.