Senior Data Engineer

singapore telecommunications limited

Singapore

On-site

SGD 60,000 - 100,000

Full time

8 days ago

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Job summary

Singtel is forming a new AI & Data Analytics unit (AIDA) to scale AI ambitions across the enterprise. The role focuses on building scalable document processing pipelines, OCR/VLM, embedding models, and knowledge ingestion for retrieval-augmented GenAI systems on a modern cloud stack.

You will implement layout-aware parsing, orchestration with tools like Kafka, LangChain, and PyMuPDF, and contribute to governance, documentation, and collaboration with senior engineers.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • 1–3 years of experience in data engineering or data platform development.
  • Hands-on experience with Python, PyTorch, PEFT, LoRA, OCR, VLM, LLM, prompting, Text-to-Speech models and SQL.
  • 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 while collaborating effectively with senior engineers and other stakeholders.
  • Strong documentation and communication skills.

Responsibilities

  • Design, build, productionize, and support scalable document parsing and content extraction pipelines on a modern hybrid cloud platform, handling PDFs, PPTX, Excel, Word, images, and more.
  • Design and implement OCR, VLM, and multimodal AI pipelines leveraging state-of-the-art models for accurate content extraction, layout understanding, and table/chart interpretation.
  • Develop and optimize embedding models, including fine-tuning and domain adaptation for organization terminology and semantic search.
  • Implement knowledge ingestion, indexing, and retrieval pipelines for RAG and agentic GenAI systems with high recall and low latency retrieval.

Skills

Python
PyTorch
PEFT
LoRA
OCR
VLM
LLM
Prompting
Text-to-Speech
SQL

Education

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

Tools

Kafka
LangChain
PyMuPDF
MSAL
LlamaIndex

Job description

Powering the Future with AIDA

To lead the next phase of our AI evolution, we’ve launched a new business unit AIDAArtificial Intelligence & Data Analytics– a strategic engine driving our transformation designed to scale our AI ambitions with precision and purpose. This marks a pivotal shift in how we operate, innovate, and serve to embed intelligence into every layer of our business.

At Singtel, this is more than a technology upgrade. It’s a strategic transformation that redefines how value is created across the enterprise core—augmenting human capabilitiesand unlocking entirely new potential. It is a transformation journey by aligning people, platforms, and processesunder one cohesive strategy. Our mission is to build AI literacy, and foster a culture where intelligence empowers people.

We welcome you to join uson a transformational journey that’s reshaping the telecommunications industry — and redefining what’s possible with AI at its core.Grow with usin a workplace that championsinnovation, embracesagility, and putshuman potentialat the heart of everything we do.

Be a Part of Something BIG!

  • Design, build, productionize, and support scalable document parsing and content extraction pipelines on a modern hybrid cloud platform, handling structured and unstructured data including PDFs, PPTX, Excel, Word, images, scanned documents, videos, audios, charts, tables etc
  • Design and implement OCR, VLM, and multimodal AI pipelines leveraging state-of-the-art models (e.g., GPT- [4/5]o, vision-language models, Text-to-Speech) for accurate content extraction, layout understanding, and table/chart interpretation
  • Develop and optimize embedding models, including fine-tuning and domain adaptation to support organization-specific terminology, keywords, and semantic search use cases
  • Implement knowledge ingestion, indexing, and retrieval pipelines for RAG (Retrieval-Augmented Generation) and agentic GenAI systems, ensuring high recall, precision, and low-latency retrieval
Make an Impact by:
  • Build and maintain data ingestion pipelines for batch and streaming data sources using tools/library like Kafka, LlamaIndex, LangChain, PyMuPDF, MSAL etc.
  • Implement layout-aware parsing to accurately preserve document structure, hierarchy, and reading order (using OCR, VLM, and multimodal AI solutions).
  • Extract accurate numeric and semantic data from complex charts and irregular tables while preventing hallucinations.
  • Assist in integrating data from diverse source systems (files, APIs, databases, streaming)
  • Implement, fine-tune, and optimize embedding models to support organization-specific terminology, improving semantic search, retrieval accuracy, and downstream GenAI performance.
  • Help maintain metadata and pipeline documentation for transparency and traceability
  • 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 cloud (Azure)
  • Implement and operate knowledge base storage, lifecycle management and embedding/vectorization
  • Contribute to automation efforts using version control and CI/CD workflows
  • Apply basic data governance and access control policies during implementation.
Skills for Success:
  • Bachelor’s degree in Computer Science, Engineering, or a related field
  • 1–3 years of experience in data engineering or data platform development. Fresh graduates encouraged to apply as well.
  • Proven ability to independently build basic batch or streaming document processing pipelines
  • Hands-on experience with Python, PyTorch, PEFT, LoRA, OCR, VLM, LLM, prompting, Text-to-Speech models 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 while collaborating effectively with senior engineers and other stakeholders
  • Strong documentation and communication skills
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