Lead Data Integration Architect

ITC Infotech; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

ITC Infotech in Singapore is seeking an experienced Lead Data Integration Architect to define end-to-end integration architectures across enterprise applications, SAP platforms, and cloud data platforms.

You will lead design workshops, govern patterns, and provide hands-on guidance to data engineering teams, ensuring scalable, secure, and high‑performing integrations.

Exposure to AI/ML data integration and modernization initiatives is highly desirable.

Qualifications

• Hands-on experience designing and delivering complex application-to-application and application-to-data-platform integrations.
• Strong knowledge of enterprise integration patterns and data movement architectures.
• Experience with SAP Datasphere, SAP S/4HANA (SD/FICO) integration.
• Experience with cloud data platforms and AI/ML ecosystems.
• Experience in multi-cloud, hybrid environments.

Responsibilities

• Design end-to-end data integration solutions across enterprise applications, SAP platforms, cloud data platforms, analytics environments, and AI ecosystems.
• Lead solution design workshops with platform application, platform, and engineering teams; review and approve designs.
• Provide hands-on guidance to data engineering teams on implementation approaches and technical design decisions.
• Troubleshoot complex integration architecture challenges and support critical project deliveries.
• Ensure integration solutions meet requirements for scalability, reliability, maintainability, performance, and security.

Skills

ETL/ELT architecture

Enterprise integration patterns

APIs (REST, GraphQL)

Data movement architectures

Spark / PySpark

Data governance and lineage

Tools

Databricks

Job description

We are seeking an experienced Lead Data Integration Architect with strong hands‑on expertise in designing and implementing enterprise‑scale data integration solutions. This role combines architecture leadership with practical integration design experience and is responsible for defining end‑to‑end application‑to‑application and application‑to‑data‑platform integration architectures across a complex enterprise landscape.

The successful candidate will have deep experience designing and governing data movement across operational systems, SAP platforms, cloud data platforms, analytics environments, and AI/ML ecosystems. They must be comfortable operating at both the strategic architecture level and the detailed solution design level, working closely with engineering teams to ensure successful delivery.

This role is particularly suited to architects who have previously worked as senior data engineers, integration leads, or solution architects and have hands‑on experience designing scalable data integration frameworks and patterns.

Key Responsibilities:

• Design end‑to‑end data integration solutions across enterprise applications, SAP platforms, cloud data platforms, analytics environments, and AI ecosystems.
• Define and govern enterprise integration patterns including:
• Batch integrations
• Near real‑time integrations
• Event‑driven architectures
• API‑based integrations
• Streaming integrations
• File‑based integrations
• Create detailed application‑to‑application, application‑to‑data‑platform, and cross‑platform integration designs.
• Define canonical data exchange patterns, integration standards, and reusable integration frameworks.
• Establish best practices for data ingestion, transformation, orchestration, and data delivery.

Solution Design & Delivery Leadership

• Lead solution design workshops with platform application, platform, and engineering teams.
• Review and approve integration solution designs produced by delivery teams.
• Provide hands‑on guidance to data engineering teams on implementation approaches and technical design decisions.
• Troubleshoot complex integration architecture challenges and support critical project deliveries.
• Ensure integration solutions meet requirements for scalability, reliability, maintainability, performance, and security.

Data Platform & Modernization

• Define integration strategies for hybrid and multi‑cloud environments.
• Design ingestion and data movement frameworks supporting structured, semi‑structured, and unstructured data.
• Support integration of SAP Datasphere, SAP S/4HANA (SD/FICO), and other enterprise systems into cloud data platforms.
• Ensure integration solutions align with enterprise architecture principles, data models, governance standards, and security requirements.
• Establish integration design standards, architecture review processes, and technical guardrails.
• Collaborate with data governance teams to support metadata management, lineage, and data quality initiatives.
• Work closely with domain data teams, platform teams, application teams, and external vendors to drive architecture consistency.
• Demonstrated experience designing complex application‑to‑application and application‑to‑platform integrations.
• Proven experience working within large‑scale enterprise environments with multiple source systems and data platforms.
• Experience supporting cloud data platform modernization and migration initiatives.
• Exposure to AI/ML, Generative AI, and Agentic AI data integration requirements is highly desirable.

Technical Skills:

• Strong hands‑on experience with ETL/ELT architecture and implementation.
• Deep understanding of enterprise integration patterns and data movement architectures.
• Batch processing solutions
• Near real‑time integrations
• Event‑driven architectures
• Strong experience with:
• APIs (REST, GraphQL)
• File‑based integrations
• Data replication technologies
• Hands‑on experience with Spark and PySpark, Notebook.
• Strong SQL development and performance optimization skills.

Data Platforms

• AWS Databricks (preferred).
• Lakehouse and Data Lake architectures.
• Experience integrating enterprise applications into modern cloud data platforms.
• Strong understanding of AWS cloud services.
• Experience with orchestration platforms:
• Databricks Workflows
• Equivalent tools
• Experience implementing CI/CD pipelines for data and integration workloads.
• Infrastructure‑as‑Code exposure is desirable.
• Data modeling (logical, conceptual, and physical).
• Master data and reference data concepts.
• Metadata, lineage, and governance frameworks.
• Data quality and data management best practices.

Enterprise Applications

• Strong understanding of SAP S/4HANA data structures and integration patterns.
• Experience integrating SAP and non‑SAP enterprise applications.
• Familiarity with enterprise business processes and operational data domains.

Preferred Qualifications:

• SAP Datasphere or SAP‑related certifications.

Candidates must demonstrate hands‑on experience designing and delivering complex application‑to‑application and application‑to‑data‑platform integrations. Pure governance‑focused Data Architects or Enterprise Architects without significant delivery and integration design experience will not be considered.