Databricks Data Engineer - Scalable Pipelines & Analytics

NCS Group; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

NCS Group in Singapore is seeking a Data Engineer to design, develop, and maintain scalable data pipelines on Databricks and cloud platforms, integrating diverse data sources and supporting analytics, reporting, and machine learning workloads.

You will collaborate with analytics, product and infrastructure teams to enhance the data platform, implement governance, monitoring, and reliability, and explore new tools such as Azure, Databricks, and related technologies.

Qualifications

• 3+ years of data engineering experience with scalable pipelines.
• Strong data modelling and distributed computing design skills.
• Hands-on PySpark, Spark SQL and Databricks notebooks/jobs experience.
• Experience orchestrating pipelines with Airflow or similar tools.
• SQL proficiency with window functions and performance optimization.
• DevOps practices, Git workflows and CI/CD familiarity.
• Familiarity with Scrum and collaborative teamwork.
• Databricks Certification (Associate/Professional) is strongly preferred.

Responsibilities

• Develop and maintain ETL pipelines for ingestion, transformation, validation and loading.
• Design data solutions with data modelling and distributed computing architectures.
• Build pipelines on Azure, with Databricks notebooks/jobs and spark-based processing.
• Collaborate with analytics, product and infrastructure teams to enhance the data platform.
• Implement data governance, monitoring, and reliability best practices.
• Develop dashboards, reports, and data visualizations to support analytics.
• Ensure data quality and perform data validation and profiling.
• Participate in requirement grooming and UAT with users and stakeholders.

Skills

PySpark

SQL

Data modeling

Distributed computing

Spark

Kafka

Real-time processing

Tools

Azure

AWS

Airflow

Databricks

Kafka

Git

Job description

NCS Group in Singapore is seeking a Data Engineer to design, develop, and maintain scalable data pipelines on Databricks and cloud platforms, integrating diverse data sources and supporting analytics, reporting, and machine learning workloads.

You will collaborate with analytics, product and infrastructure teams to enhance the data platform, implement governance, monitoring, and reliability, and explore new tools such as Azure, Databricks, and related technologies.