Data Engineer (Content Processing)

Csit
Singapore
On-siteCareer-pivot friendly

Who this role is best for

Strong fit for mid-level data engineers with AI integration experience who architect pipelines for unstructured data processing in national security. Collaboration with cross-functional teams and expertise in hybrid retrieval systems are critical for success in Singapore's cloud-native environment.

Best fit for

  • Mid-level engineers with ETL/ELT pipeline experience and AI model integration skills in national security domains
    — “proven hands-on experience in data engineering or software development”
  • Candidates who have built hybrid indexing systems combining keyword and semantic search for large datasets
    — “Build and support robust hybrid indexing systems that seamlessly combine high-speed keyword search with vector-based semantic search”
  • Individuals with background in processing high-volume unstructured data and optimizing transformation logic
    — “Data Pipeline Engineering: Architect, design, and maintain reliable, high-throughput pipelines that ingest, route, and process vast volumes of unstructured data”

Things to consider

  • Citizenship requirement restricts eligibility to Singapore Citizens only
    — “only Singapore Citizens will be considered”
  • Role demands expertise in both traditional data engineering and emerging AI/ML technologies
    — “architect intelligent systems that ingest unstructured data, generate vector embeddings, and unlock semantic search capabilities”

How to stand out

  • Highlight experience with vector databases and semantic search frameworks in resume projects
    — “Exposure to vector databases, text embedding techniques, LLM integration, or semantic search frameworks”
  • Demonstrate pipeline optimization achievements with metrics on latency and throughput improvements
    — “ensuring latency and throughput meet mission-critical standards”
  • Showcase cross-team collaboration examples with data scientists and product managers
    — “Partner closely with frontend engineers, data scientists, and product managers”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Mid

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Architect, design, and maintain reliable, high-throughput pipelines
  • Develop and optimize transformation logic
  • Build and support robust hybrid indexing systems
  • Engineer scalable solutions for video analysis and image recognition
  • Uphold rigorous data quality and pipeline reliability standards
Typical background
Background in Computer Science or a related fieldExperience in building scalable ETL/ELT pipelinesGood grasp of data quality principles

Skills & requirements

Required

Data Pipeline EngineeringData TransformationHybrid Retrieval SystemsMultimedia ProcessingEngineering ExcellenceCross-functional Collaboration

Preferred

Vector DatabasesText Embedding TechniquesLLM IntegrationSemantic Search FrameworksContainer-based EnvironmentsMultimedia Processing ToolsComputer Vision LibrariesHandling High-volume, Unstructured Data In Cloud-native Environments

Stack & domain

Data Pipeline EngineeringEtl/elt PipelinesData TransformationVector EmbeddingsHybrid Retrieval SystemsMultimedia ProcessingAI ModelsCloud-native EnvironmentsProblem-solvingInnovationCollaborationCommunicationTeamworkQuality AssuranceData EngineeringNational SecurityAICloud Computing

About the role

Original posting from Csit via Lever

CSIT develops cutting-edge products to safeguard Singapore's national security interests. We are seeking Data Engineers to join a specialized team operating at the heart of our mission, transforming hundreds of thousands of documents daily through large-scale pipelines. In this role, you will go beyond traditional data engineering; you will architect intelligent systems that ingest unstructured data, generate vector embeddings, and unlock semantic search capabilities to uncover critical insights from massive datasets. Your work will directly power the next generation of analytical products, enabling our analysts to detect threats across critical domains, including but not limited to Cybersecurity.

Key Responsibilities:

  • Data Pipeline Engineering: Architect, design, and maintain reliable, high-throughput pipelines that ingest, route, and process vast volumes of unstructured data. You will integrate AI models for automated data classification and information extraction, while ensuring latency and throughput meet mission-critical standards.
  • Data Transformation & Enrichment: Develop and optimize transformation logic that parses complex content, implements chunking strategies, and generates high-quality vector embeddings for downstream retrieval. You will ensure data is enriched and structured for maximum analytical value.
  • Hybrid Retrieval Systems: Build and support robust hybrid indexing systems that seamlessly combine high-speed keyword search with vector-based semantic search. You will engineer solutions that allow analysts to retrieve precise insights from enriched content instantly.
  • Multimedia Processing: Engineer scalable solutions for video analysis and image recognition, integrating computer vision models to extract actionable metadata from diverse media formats within our data streams.
  • Engineering Excellence: Uphold rigorous data quality and pipeline reliability standards while actively contributing innovative ideas to leverage AI for scaling operations. You will champion best practices in code quality, testing, and system observability.
  • Cross-Functional Collaboration: Partner closely with frontend engineers, data scientists, and product managers to deliver seamless, high-performance data services that meet the rigorous needs of national security operations.

Requirements (Minimum Qualifications):

  • Background in Computer Science or a related field, with proven hands-on experience in data engineering or software development.
  • Experience in building scalable ETL/ELT pipelines to process, transform, and validate large datasets.
  • Good grasp of data quality principles, pipeline reliability patterns, and the ability to communicate complex technical concepts clearly.

Nice-to-haves:

  • Exposure to vector databases, text embedding techniques, LLM integration, or semantic search frameworks (curiosity and a willingness to master AI concepts are highly valued).
  • Familiarity with container-based environments (Docker/Kubernetes) and modern CI/CD practices.
  • Experience with multimedia processing tools or computer vision libraries.
  • Background in handling high-volume, unstructured data in cloud-native environments.

Why Join Us?:

  • Work that matters: Your pipelines will directly support Singapore's national security by turning raw data into actionable insights.
  • Cutting-edge tech: Gain hands-on experience deploying AI solutions and modern, cloud-native data technologies at meaningful scale.
  • Collaborative culture: Join a talented team with a strong engineering ethos and a commitment to real work-life balance.
  • Room to grow: We invest in our engineers, creating space for you to innovate in the intersection of data engineering and artificial intelligence.

As CSIT is an agency under the Ministry of Defence (Singapore), only Singapore Citizens will be considered.

Source: Csit careers (Lever)

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