Senior Data Engineer

Intellect Minds Pte Ltd; Singapore; Hybrid; SGD 120,000 - 180,000; Full time

Job summary

Intellect Minds Pte Ltd is seeking a Senior Data Engineer to design and deliver scalable data platforms across Microsoft Azure and AWS ecosystems. You will build high-performance data pipelines, data lakes, and real-time ingestion frameworks using PySpark and Databricks.

The role requires 5+ years in data engineering, strong PySpark/Databricks skills, and hands-on cloud experience. You will collaborate with architects, engineers, and business stakeholders to ensure data quality, security, and

Qualifications

• 5+ years of experience in Data Engineering.
• Strong hands-on experience with Azure and/or AWS data platforms.
• Excellent PySpark and Databricks experience.
• Strong knowledge of Data Lakes, ETL/ELT, and real-time data ingestion.
• Experience with SQL and Python.
• Knowledge of Apache Spark and distributed data processing.
• Experience with cloud data services and data architecture.
• Good understanding of CI/CD, Git, and Agile methodologies.

Responsibilities

• Design and develop scalable data platforms on Azure and AWS.
• Build and optimize high-performance ETL/ELT pipelines using PySpark and Databricks.
• Develop and manage cloud-based data lakes and data warehouses.
• Design real-time and batch data ingestion frameworks.
• Implement data processing solutions using Apache Spark/PySpark.
• Optimize data pipelines for performance, scalability, and reliability.
• Work with cloud services such as Azure Data Factory, ADLS, Azure Synapse, AWS S3, Glue, and EMR.
• Implement data quality, security, monitoring, and governance standards.
• Collaborate with Data Architects, Engineers, and business stakeholders.

Skills

Data Engineering

Azure/AWS

PySpark/Databricks

Data Lakes/ETL/Real-time

SQL & Python

Apache Spark

Cloud data services

CI/CD & Agile

Tools

Databricks

Azure Data Factory

AWS Glue

SQL

Job description

Job Summary

We are looking for a Senior Data Engineer with strong experience designing and delivering scalable data platforms across Microsoft Azure and AWS ecosystems. The candidate will be responsible for building high-performance data pipelines, data lakes, and real-time data ingestion frameworks using PySpark and Databricks.

Key Responsibilities

• Design and develop scalable data platforms on Azure and AWS.

• Build and optimize high-performance ETL/ELT pipelines using PySpark and Databricks.

• Develop and manage cloud-based data lakes and data warehouses.

• Design real-time and batch data ingestion frameworks.

• Implement data processing solutions using Apache Spark/PySpark.

• Optimize data pipelines for performance, scalability, and reliability.

• Work with cloud services such as Azure Data Factory, ADLS, Azure Synapse, AWS S3, Glue, and EMR.

• Implement data quality, security, monitoring, and governance standards.

• Collaborate with Data Architects, Engineers, and business stakeholders.

Required Skills

• 5+ years of experience in Data Engineering.

• Strong hands-on experience with Azure and/or AWS data platforms.

• Excellent PySpark and Databricks experience.

• Strong knowledge of Data Lakes, ETL/ELT, and real-time data ingestion.

• Experience with SQL and Python.

• Knowledge of Apache Spark and distributed data processing.

• Experience with cloud data services and data architecture.

• Good understanding of CI/CD, Git, and Agile methodologies.

Preferred Skills

• Azure Data Factory / Azure Synapse / ADLS

• AWS S3 / Glue / EMR

• Kafka or other real-time streaming technologies

• Delta Lake

• Terraform / Infrastructure as Code

• Data governance and security