Assistant Manager - Microsoft - Data & AI (Data Engineering) | Hybrid - Makati

Roles & responsibilities 

• Design, build, and maintain scalable data solutions on Microsoft Azure to support business data needs. 
• Presales support to help KPMG bid for modern data platforms projects.
• Develop and manage data pipelines for ingesting, transforming, and integrating data from multiple sources.
• Implement data security, governance, and privacy controls across Azure data platforms.
• Monitor, troubleshoot, and optimize data workflows to ensure reliability, performance, and cost efficiency. 
• Optimize data storage and processing solutions by leveraging Azure best practices and services
• An Azure Data Engineer is responsible for designing, building, and maintaining scalable data framework on the Azure data requirements. The role involves developing and managing end‑to‑end data pipelines, integrating data from multiple sources, and ensuring reliable data ingestion, transformation and processing using pyspark. The Azure Data Engineer also implements data security, privacy, and governance controls, monitors and troubleshoots data workflows, and continuously optimizes data storage and processing to achieve high performance and cost efficiency across Azure data platforms
  

Educational qualifications 

• Graduate or postgraduate in Computer Science Engineering Specialization. 

Work experience

• 7 - 10 years hands-on experience in software development with significant focus on Azure Data Engineering

Mandatory  technical & functional skills

• Bachelor’s degree in Computer Science or related field, or equivalent experience (10+ years), with demonstrated leadership and stakeholder management capabilities, including proposal/RFP support.
• Strong experience leading and managing data engineering teams and delivering client‑facing consulting engagements on Azure data platforms (5+ years). 
• Proven expertise in designing and building data ingestion, processing, and analytics pipelines across SQL Server, Azure Synapse, Azure Databricks, and Microsoft Fabric (including 2+ years with Fabric). 
• Extensive hands-on experience with Azure ETL, Data modelling  and data processing services, including Fabric OneLake/Lakehouse/Warehouse, ADLS, Azure Data Factory, Azure Functions, and Fabric components. 
• Deep technical experience with Azure and Big Data technologies such as Fabric, Databricks, Synapse, Python, SQL, ADLS/Blob Storage, PySpark, and Spark SQL, along with RDBMS expertise (3+ years). 
• Experience with big data file formats, compression techniques, and CI/CD & development tools such as Azure DevOps, Git, and Visual Studio Team Services (VSTS).

Preferred technical & functional skills 

• Technical leadership and solution architecture experience in designing Azure data platforms, leading data engineering teams, and delivering client‑facing demos and presentations with strong business communication skills.
• Proven expertise in designing and deploying scalable ETL solutions on Azure using Azure Data Factory, Synapse Analytics, Azure Functions, and Notebooks, ensuring secure and efficient data workflows.
• Strong hands‑on experience with Microsoft Fabric, including Medallion Architecture, metadata‑driven ingestion, data quality frameworks, and SCD Type 1 & Type 2 transformations using Fabric Notebooks or Databricks.
• Exposure to Microsoft Copilot and Generative AI, with the ability to identify and apply industry‑relevant use cases to enhance data engineering and analytics workflows.
• Proficiency in Data modelling and building large scale Datawarehouse design.
• Proficiency in Power BI for building dashboards and KPIs, along with solid knowledge of Azure RBAC, IAM, and data security/compliance practices.
• Experience with data governance, performance optimization, Azure DevOps/Git, mentoring teams, and alignment with Microsoft’s data and AI roadmap; cross‑cloud or hybrid experience is a plus.