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Open nowPosted 2 days ago

Data & Integration Engineer, AI (Banking, 1-year renewable contract)

EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD.

Pay
SGD 5,000 – SGD 8,500 a month
Where
Singapore
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Your applicationOpen nowData & Integration Engineer, AI (Banking, 1-year renewable contract)EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD. · Singapore

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD.'s own form.

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 2 days ago

The posting

Dear Applicant,

If you or someone you know is interested, please send the CV directly to [email protected] (most preferred, as I may overlook some CVs due to the high volume).

Please note that visa sponsorship is not available at this time.

Key Responsibilities

• Analyse business and technical requirements and translate them into end-to-end data flows, integration designs, interface specifications, and implementation plans.

• Collaborate with upstream and downstream teams to define data contracts, interfaces, and integration requirements.

• Identify gaps, inefficiencies, and risks in existing data movement processes, proposing practical solutions that balance delivery speed, quality, and maintainability.

• Design and implement data integrations across enterprise systems using REST APIs, SFTP, file-based transfers, and batch processing.

• Develop scripts and programs to retrieve, process, transform, and transfer data across different integration systems.

• Develop and maintain APIs to enable seamless integration between applications, data platforms, and downstream systems.

• Coordinate data integrations across enterprise data platforms, including Informatica, Cloudera, and similar technologies.

• Ensure data is accurately mapped, transformed, aggregated, reconciled, and delivered to target systems in the required format.

• Support data ingestion and preparation for Generative AI (GenAI) use cases, including document ingestion, data enrichment, aggregation, and transformation.

• Work with structured and unstructured data to ensure it is suitable for downstream AI workflows, including Retrieval-Augmented Generation (RAG), search, and investigation use cases.

• Collaborate with data platform, application, infrastructure, and security teams to deliver reliable end-to-end integrations.

• Troubleshoot integration and data pipeline issues across different environments, ensuring appropriate error handling, monitoring, and recovery mechanisms.

• Support System Integration Testing (SIT), User Acceptance Testing (UAT), and production deployments.

• Maintain clear documentation of data flows, mappings, interfaces, and integration processes.

Key Requirements

• Min 4 years of experience in system analysis, integration engineering, data engineering, or technical delivery roles.

• Strong ability to translate business and technical requirements into system flows, data flows, interface specifications, and implementation plans.

• Experience delivering enterprise integrations and coordinating with upstream and downstream teams.

• Hands-on experience with REST APIs, SFTP, batch processing, file-based integrations, and data pipeline orchestration.

• Good understanding of data mapping, transformation, aggregation, reconciliation, and data quality controls.

• Strong SQL skills and basic to intermediate Python programming skills for data processing, scripting, automation, and troubleshooting.

• Exposure to Java programming.

• Experience with enterprise data platforms such as Informatica, Cloudera, or equivalent technologies. Working experience with Informatica is preferred.

• Working knowledge of Git, branching strategies, pull requests, code reviews, and controlled release practices.

• Familiarity with CI/CD pipelines, Jira, Confluence, and enterprise deployment processes.

• Experience with Control-M or equivalent job scheduling tools.

• Familiarity with logging and monitoring tools, such as OpenTelemetry (OTel), Splunk, or Elastic Stack.

• Exposure to GenAI concepts, including document ingestion, RAG, embeddings, and data preparation for AI workflows.

• Strong analytical and problem-solving skills, with the ability to challenge ineffective designs and recommend practical alternatives.

• Excellent communication and stakeholder management skills, with the ability to coordinate across business, application, data, infrastructure, and security teams.

• A strong understanding of end-to-end system flows and the ability to troubleshoot and implement solutions in complex enterprise environments.

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