NCS PTE. LTD. Hiring! Full Time Senior Data Engineer in Central Region (Singapore), Earn up to SGD 6,000 - Ricebowl

"Data Pipeline Development &Operations
•  Design, build, and operate scalable and reliable data pipelines on theDatabricks platform
•  Develop end-to-end data workflows from ingestion through transformation toconsumption
•  Implement robust error handling, monitoring, and alerting mechanisms
•  Ensure data pipeline reliability, performance, and maintainability
•  Optimize pipeline performance through efficient Spark job design and clusterconfiguration
•  Manage and orchestrate complex data workflows using Databricks Jobs andworkflows

Legacy Code Modernization
•  Refactor legacy code and data pipelines to PySpark for improved performanceand scalability
•  Migrate traditional ETL processes to modern ELT patterns on Databricks
•  Assess existing codebases and identify opportunities for optimization andmodernization
•  Ensure backward compatibility and data integrity during migration processes
•  Document refactoring approaches and create migration playbooks
•  Collaborate with stakeholders to minimize disruption during code transitions

Data Engineering Excellence
•  Implement data quality checks and validation frameworks
•  Design and maintain Delta Lake tables with appropriate optimizationstrategies
•  Develop reusable code libraries and frameworks for common data engineeringtasks
•  Follow software engineering best practices including version control,testing, and CI/CD
•  Participate in code reviews and provide constructive feedback to teammembers
•  Troubleshoot and resolve data pipeline issues in production environments

Collaboration & Knowledge Sharing
•  Work closely with data architects, analysts, and business stakeholders
•  Collaborate with Infrastructure (Infra), Applications (Apps), and Cyberteams
•  Share knowledge and best practices with Team NCS
•  Mentor junior data engineers on PySpark and Databricks technologies
•  Document technical solutions and maintain comprehensive documentation"  "EssentialTechnical Skills
•  Data Engineering: Strong foundation in data engineering principles, ETL/ELTprocesses, and data pipeline design patterns
•  PySpark: Proven hands-on experience developing data pipelines using PySpark,including DataFrames API, Spark SQL, and performance optimization
•  Databricks Platform: Practical experience with Databricks workspace, clustermanagement, notebooks, and job orchestration
•  Workspace AI Agent: Knowledge of Databricks Workspace AI Agent capabilitiesand integration
•  Data Modelling: Experience implementing data models including dimensionalmodeling, data vault, or lakehouse architectures
•  Delta Lake: Understanding of Delta Lake features including ACIDtransactions, schema evolution, and optimization techniques
•  Python: Strong Python programming skills for data processing and automation

Additional Technical Skills
•  SQL proficiency for data querying and transformation
•  Experience with cloud platforms (Azure, AWS, or GCP)
•  Understanding of data governance and security best practices
•  Knowledge of streaming data processing (Structured Streaming)
•  Familiarity with DevOps practices and CI/CD pipelines
•  Experience with version control systems (Git)
•  Understanding of data quality frameworks and testing methodologies

Professional Experience
•  Minimum 8 years in data engineering or related roles
•  At least 2-3 years of hands-on experience with Databricks platform
•  Proven track record of refactoring legacy code to modern frameworks
•  Experience building and maintaining production data pipelines at scale
•  Background working across multiple data sources and formats
•  Experience in agile development environments

Required Certifications - mandatory to haveat least one certification
•  Databricks Certified Data Engineer Associate OR Databricks Certified DataEngineer Professional

Additional Certifications (Preferred)
•  Databricks Certified Associate Developer for Apache Spark
•  Cloud platform certifications (Azure Data Engineer Associate, AWS CertifiedData Analytics, or Google Cloud Professional Data Engineer)
•  Relevant data engineering or big data certifications

Soft Skills
•  Strong problem-solving and analytical thinking abilities
•  Excellent communication skills to explain technical concepts clearly
•  Ability to work collaboratively in cross-functional teams
•  Self-motivated with strong attention to detail
•  Adaptable to changing priorities and technologies
•  Client-focused mindset with commitment to quality delivery"

"Minimum 8 years and above ofexperience.