Senior AI Data Engineer (Ref 26570)

JOBLINE RESOURCES PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

JOBLINE RESOURCES PTE. LTD. is seeking a Data Platform Engineer in Singapore to design, build, and operate production-grade batch and streaming data pipelines using Databricks and Kafka.

You will transform data with PySpark/SQL, ensure data quality, and drive observability and governance across the platform. Key responsibilities include leading ingestion from diverse sources, mentoring engineers, and coordinating with source-system teams to enable secure, scalable solutions.

Qualifications

• Bachelor's degree or higher in CS/Engineering or related field.
• 5–8 years of data engineering or cloud-scale analytics experience with production pipelines.
• Proven ability to design, build, optimise, and operate production-grade data pipelines.
• Hands-on Python and SQL for data transformation and validation.
• Familiarity with PySpark and Spark concepts at scale.
• Experience with knowledge base and RAG solutions for AI use cases.
• Strong problem-solving, communication, and leadership in technical discussions.

Responsibilities

• Design, build, optimise, and maintain batch and streaming pipelines with Databricks and Kafka.
• Perform data transformation using PySpark or SQL.
• Monitor and troubleshoot data workflows for quality and reliability.
• Guide engineers and delivery partners on platform patterns and code quality.
• Lead ingestion from files, APIs, databases, and streaming sources with defined patterns.
• Maintain metadata and pipeline documentation for transparency.
• Own production readiness, observability, incident triage, and runbook improvements.
• Integrate pipelines with Microsoft Fabric, Databricks, Delta Lake, and other components.
• Develop and maintain knowledge base and RAG solutions across hosting platforms.
• Implement knowledge base storage, lifecycle management, and embeddings.

Skills

Python

SQL

PySpark

Apache Spark

Databricks

Kafka

CI/CD

Observability

Data governance

Communication

Education

Bachelor's degree in Computer Science/Engineering

Tools

Microsoft Fabric

Databricks

Delta Lake

Job description

Responsibilities

• Design, build, optimise, and maintain batch and streaming data ingestion pipelines using platforms such as Databricks and Kafka, ensuring scalability, reliability, observability, and alignment with enterprise data architecture standards.
• Perform data transformation and cleansing using PySpark or SQL based on business and technical requirements
• Monitor and troubleshoot data workflows to ensure data quality and pipeline reliability
• Provide technical guidance to engineers and delivery partners on data platform patterns, reusable components, code quality, deployment readiness, and production support practices.
• Lead integration of data from diverse source systems including files, APIs, databases, and streaming platforms, working with source-system owners and consuming teams to define fit-for-purpose ingestion patterns and delivery timelines.
• Help maintain metadata and pipeline documentation for transparency and traceability
• Own production readiness for assigned data and AI platform components, including observability, incident triage, root-cause analysis, release coordination, and continuous improvement of operational runbooks.
• Participate in integrating pipelines with tools such as Microsoft Fabric, Databricks, Delta Lake, and other platform components
• Build and maintain knowledge base and RAG solution on variety of hosting platforms
• Implement and operate knowledge base storage, lifecycle management and embedding/vectorization
• Contribute to automation efforts using version control and CI/CD workflows
• Apply data governance, security, access control, and operational risk policies during solution design and implementation, ensuring pipelines and knowledge platforms meet enterprise compliance requirements.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field
• 5-8 years of experience in data engineering, data platform engineering, or cloud-scale analytics solution delivery, with demonstrated ownership of production pipelines and platform components.
• Proven ability to independently design, build, optimise, and operate production-grade batch or streaming data pipelines, including orchestration, observability, error handling, performance tuning, and operational support.
• Hands-on experience with Python and SQL for data transformation and validation
• Familiarity with Apache Spark (especially PySpark) and large-scale data processing concepts
• Experience with implementing knowledge base and RAG solutions for agentic AI use cases
• Self-starter with strong problem-solving skills and a keen attention to detail
• Able to work independently and lead technical discussions with engineers, architects, product owners, source-system teams, and business stakeholders to translate requirements into secure and maintainable platform solutions.
• Strong documentation and communication skills
• Strong understanding of enterprise data architecture, cloud security, access control, CI/CD, release management, and production operations for data and AI platform solutions.

Licence no: 12C6060