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

EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Evolution Recruitment Solutions Pte. Ltd. is seeking an experienced Integration Engineer to translate business and technical requirements into end-to-end data flows.

You will design, implement, and troubleshoot data integrations across enterprise systems using REST APIs, SFTP, and batch processing, while coordinating across data platform, application, and security teams. You will work with GenAI ingestion and AI workflows, ensuring data quality, mapping, and transformation across Informatica and

Qualifications

• 4+ years of experience in system analysis, integration engineering, data engineering, or technical delivery roles.
• Strong ability to translate requirements into system/data flows and designs.
• Experience delivering enterprise integrations and coordinating with upstream and downstream teams.
• Hands-on with REST APIs, SFTP, batch processing, and file-based integrations.
• Good understanding of data mapping, transformation, reconciliation, and quality controls.
• Strong SQL and Python for data processing, scripting, automation, and troubleshooting.
• Exposure to Java programming.

Responsibilities

• Analyse requirements and translate them into end-to-end data flows and implementation plans.
• Collaborate with upstream and downstream teams to define data contracts and interfaces.
• Identify gaps and propose practical, maintainable solutions balancing speed and quality.
• Design and implement data integrations using REST APIs, SFTP, batch processing, and file transfers.
• Develop scripts to retrieve, process, transform, and transfer data across systems.
• Develop and maintain APIs for seamless integration between apps and data platforms.
• Coordinate integrations across Informatica, Cloudera, and similar platforms.
• Ensure data is mapped, transformed, aggregated, reconciled, and delivered correctly.
• Support data ingestion/prep for GenAI use cases including document ingestion and enrichment.
• Work with GenAI-related data for retrieval-augmented generation and AI workflows.
• Troubleshoot integration/data pipeline issues and maintain error handling and monitoring.
• Support SIT, UAT, and production deployments.
• Maintain clear documentation of data flows and mappings.

Skills

SQL

Python

Java

Data integration

Analytical thinking

Stakeholder mgmt

Communication

Tools

Informatica

Cloudera

Git

Jira

Confluence

OpenTelemetry

Splunk

Elastic Stack

Control-M

Job description

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.