Senior AI Data Engineer

jobline resources pte. ltd.; Singapore; On-site; SGD 90,000 - 180,000; Full time

Job summary

jobline resources pte. ltd. in Singapore seeks an experienced Data Platform Engineer to design, build, and operate production-grade batch and streaming pipelines. You will transform data with Python/SQL, ensure reliability, and guide multiple teams on platform patterns and deployment readiness.

You will lead integration from diverse sources, maintain metadata, and boost observability and incident response. Experience with PySpark, Spark, Databricks, and knowledge-base/RAG solutions is essential.

Qualifications

• 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.
• Proven ability to independently design, build, optimise, and operate production‑grade batch or streaming data pipelines.
• 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.
• Strong documentation and communication skills.
• Able to lead technical discussions with engineers, architects, and product owners to translate requirements into secure platform solutions.

Responsibilities

• Design, build, optimise, and maintain batch and streaming data pipelines.
• Transform and cleanse data using PySpark or SQL.
• Monitor and troubleshoot data workflows for data quality and reliability.
• Provide technical guidance on data platform patterns, reusable components, and deployment readiness.
• Lead integration of data from diverse source systems (files, APIs, databases, streaming).
• Maintain metadata and pipeline documentation for transparency and traceability.
• Own production readiness for data and AI platform components including observability and incident triage.
• Integrate pipelines with tools like Microsoft Fabric, Databricks, Delta Lake.
• Build and maintain knowledge base and RAG solutions across hosting platforms.
• Implement knowledge base storage, lifecycle management, and embedding/vectorization.
• Contribute to automation with version control and CI/CD workflows.
• Apply data governance, security, access control, and compliance.

Skills

Python

SQL

PySpark

Apache Spark

Databricks

Kafka

Data pipelines

CI/CD

Education

Bachelor’s degree in Computer Science, Engineering, or a related field

Tools

Databricks

Kafka

Delta Lake

CI/CD

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