Databricks Engineer

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

Job summary

Basil Technologies Pte. Ltd. is seeking a Databricks Engineer to design, develop, and maintain scalable data pipelines on Databricks and cloud platforms.

You will integrate diverse data sources, ensure high-quality processing, and support analytics, reporting, and ML workloads. Collaboration with analytics, product, and infrastructure teams is essential to enhance the data platform while ensuring governance, monitoring, and reliability.

Qualifications

• 3+ years in data engineering with scalable pipelines
• Experience with data modeling and distributed computing architectures
• Hands-on data processing with PySpark, Spark SQL, and Databricks notebooks/jobs
• Experience orchestrating data pipelines with ADF, Airflow, or similar tools
• Experience with real-time and batch data processing
• Pipelines on Azure; AWS experience is a plus
• Proficient SQL including window functions and performance optimization
• Understanding of DevOps tools, Git workflows, and CI/CD pipelines
• Familiarity with Scrum and working in Scrum teams
• Ability to apply Scrum practices in projects
• Strong problem-solving and collaborative mindset
• Experience with streaming tech (Kafka, Flink, Kinesis) and real-time pipelines
• Ability to design and implement real-time data processing pipelines

Responsibilities

• Develop and maintain ETL pipelines for centralized data storage systems (e.g. Delta Lake)
• Integrate data from databases, APIs, logs, streaming platforms, and external providers
• Transform data to clean, normalize, and aggregate datasets
• Apply data processing techniques for complex or inconsistent data
• Contribute to frameworks and best practices for code development and deployment
• Implement data governance aligned with company standards
• Partner with analytics and product leaders to design and operationalize pipelines
• Collaborate with infrastructure leaders to advance cloud-based data platforms
• Explore new tools leveraging Azure, Databricks, or related platforms
• Monitor pipelines to detect and resolve issues promptly
• Develop monitoring tools, alerts, and automated error-handling
• Analyze business requirements and identify data extraction needs
• Attend refinement sessions with users
• Develop and maintain ETL pipelines for ingestion, transformation, validation, and loading
• Optimize performance and batch scheduling
• Develop dashboards, reports, scorecards, and data visualizations
• Perform SIT, data profiling and ensure data accuracy
• Validate completeness and consistency of ETL loads
• Support UAT and production implementation

Skills

ETL pipelines

Delta Lake

Azure

Databricks

PySpark

Spark SQL

Airflow

SQL

Data governance

CI/CD

Scrum

Kafka/Flink/Kinesis

Python

Collaboration

Tools

ADF

Git

CI/CD tools

Job description

Job Role Name: Databricks Engineer

Qualifications

• 3 or more years of experience in data engineering with scalable pipelines
• Strong experience designing data solutions including data modelling and distributed computing architectures
• Hands-on experience with data processing jobs using PySpark, Spark SQL, and Databricks notebooks/jobs
• Experience orchestrating data pipelines with ADF, Airflow, or similar tools
• Experience with both real-time and batch data processing
• Experience building pipelines on Azure, with AWS experience beneficial
• Proficiency in SQL including window functions and performance optimization
• Understanding of DevOps tools, Git workflows, and CI/CD pipelines
• Familiarity with Scrum methodology and experience working in Scrum teams
• Ability to apply Scrum practices in a practical project context
• Strong problem-solving and collaborative mindset
• Experience with streaming technologies such as Apache Kafka, Apache Flink, or AWS Kinesis
• Ability to design and implement real-time data processing pipelines

Certification:

Databricks Certified Data Engineer Associate and Databricks Certified Data Engineer Professional are preferred.

Job Description

The Data Engineer will be responsible for designing, developing, and maintaining scalable and reliable data pipelines on Databricks and cloud platforms. The role requires integrating diverse data sources, ensuring high-quality data processing, and supporting analytics, reporting, and machine learning workloads. The role involves collaborating closely with analytics, product, and infrastructure teams to enhance the company’s data platform while adhering to best practices for governance, monitoring, and reliability.

What will you do?

• Develop and maintain ETL pipelines for centralized data storage systems (e.g. Delta Lake).
• Integrate data from databases, APIs, log files, streaming platforms, and external providers
• Develop data transformation routines to clean, normalize, and aggregate data
• Apply data processing techniques to handle complex or inconsistent datasets
• Contribute to frameworks and best practices for code development and deployment
• Implement data governance in alignment with company standards
• Partner with analytics and product leaders to design and operationalize pipelines
• Collaborate with infrastructure leaders to advance cloud-based data platforms
• Explore new tools and techniques leveraging Azure, Databricks, or related platforms
• Monitor data pipelines to detect and resolve issues promptly
• Develop monitoring tools, alerts, and automated error-handling mechanisms
• Analyze business requirements and identify data extraction requirements
• Attend and refinement sessions with users
• Develop and maintain ETL pipelines for ingestion, transformation, validation, and loading
• Optimize performance and batch scheduling
• Develop dashboards, reports, scorecards, and data visualizations
• Perform SIT, data profiling and confirm data accuracy
• Validate completeness and consistency of ETL Loads
• Support UAT and production implementation