Data & AI Solutions Specialist

re-zoo-me; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Job summary

re-zoo-me in Singapore seeks a senior data engineer to design, develop, and optimize scalable data pipelines leveraging Big Data, cloud, and AI technologies. You will work with architects, data scientists, and engineers to deliver production-ready solutions for complex business use cases.

Responsibilities include building batch and real-time pipelines with Spark/PySpark, SQL, Python; deploying ETL/ELT processes; integrating AWS services; and implementing CI/CD with Docker, Kubernetes, and

Qualifications

• Bachelor's or master's degree in a related field and strong data engineering foundation.
• 8+ years of hands-on data engineering experience with large-scale processing.
• Proficient in Python, Java, or Scala and SQL.

Responsibilities

• Design and maintain scalable batch and real-time data pipelines.
• Build ETL/ELT processes for large datasets.
• Create data ingestion solutions from databases, APIs, files, and streams.
• Work with AWS services like S3, Glue, EMR, Redshift, and Kinesis.
• Develop data processing using Hadoop, Hive, Spark, Kafka, Cloudera, and Databricks.
• Tune SQL and Spark workloads for performance.
• Design data models, warehouses, and data lakes.
• Develop CI/CD pipelines; support Docker, Kubernetes, OpenShift deployments.
• Incorporate generative AI, NLP, LLMs, and vector databases as needed.
• Collaborate with architects, data scientists, and stakeholders to deliver production‑ready solutions.
• Participate in design, development, testing, deployment, and production support.

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 technologies

Education

Bachelor's or Master's degree in Computer Science, IT, Engineering, or related field

Tools

AWS

S3

Glue

EMR

Redshift

Kinesis

Lambda

Airflow

Jenkins

Docker

Kubernetes

OpenShift

Snowflake

MongoDB

Oracle

PostgreSQL

Generative AI technologies

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
• Generative AI technologies