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

Evolution Singapore; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Evolution Singapore is seeking an experienced Data Integration Specialist to translate requirements into robust data flows and integration designs. You will collaborate across teams to define interfaces, implement REST APIs and batch pipelines, and ensure accurate data delivery for AI-related workloads.

The role requires hands-on experience with Informatica/Cloudera, strong SQL and Python skills, and excellent stakeholder communication to drive reliable end-to-end solutions in a dynamic

Qualifications

• Four+ years in system analysis or data integration delivery roles.
• Ability to translate requirements into data flows and interfaces.
• Experience delivering enterprise integrations with cross-team collaboration.
• Hands-on REST APIs, SFTP, batch processing, and data pipelines.
• Strong SQL and Python for data processing and automation.
• Exposure to Java and enterprise data platforms (Informatica, Cloudera).
• Knowledge of Git, Jira, Confluence, and CI/CD practices.
• GenAI concepts for data prep and AI workflows.
• Excellent communication and stakeholder management.

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.

Skills

SQL

Python

Java

ETL / data integration

REST APIs

SFTP

Data mapping

Data quality controls

CI/CD

Git

GenAI data workflows

Communication

Tools

Informatica

Cloudera

Control-M

Git

Jira

Confluence

CI/CD tools

Job description

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.