全职 Data Integration Architect 工作, 薪水 up to SGD 11,000, Lavu Tech Solutions 公司招聘中 - Ricebowl

Job Title

Data Integration Architect / Lead

Location

Singapore

Role Summary

Seeking a Data Integration Architect / Lead who combines enterprise data architecture expertise with hands‑on data integration leadership. This role is responsible for designing end‑to‑end application‑to‑application data flows and guiding data integration delivery.

The ideal candidate operates equally comfortably at architectural design level and solution delivery level.

Key Responsibilities

• Design end‑to‑end data flows across enterprise applications and analytics platforms
• Define and apply batch, near‑real‑time, and event‑driven integration patterns
• Lead integration design and guide engineering teams on implementation best practices
• Ensure data integrations align with enterprise data architecture, models, and standards
• Support platform modernization from Azure Synapse to AWS Databricks, including hybrid/co‑existence patterns
• Review and approve data integration designs for scalability, reliability, security, and governance
• Act as a bridge between Enterprise Data Architects and Data Engineering teams

Qualifications

Experience Range

12–14 years of total experience, with:

• 8+ years in data integration / data engineering
• 3+ years in a data architecture or solution design role
• Proven experience working in enterprise‑scale data environments
• Prior involvement in data platform modernization or cloud migration initiatives preferred

Data Platforms

• Azure Synapse Analytics
• AWS Databricks (target / modernization platform)
• Data lakes and lakehouse architectures

Data Integration & Processing

• ETL / ELT frameworks
• Spark / PySpark
• Batch and near‑real‑time processing
• APIs, messaging, and file‑based integrations

Cloud & DevOps

• Azure and AWS core services (storage, compute, networking)
• Orchestration tools (ADF, Airflow, or equivalent)
• CI/CD for data pipelines

Data & Architecture

• SQL and data modeling (logical & physical)
• Enterprise data architecture principles
• Data governance, metadata, and lineage concepts (desirable)
• Solid experience designing application‑to‑application data flows
• Experience working in large‑scale enterprise environments