Microsoft Fabric Data Engineer

Directio is a global IT services company. We consult, code, test, deploy, and manage mainly cloud-based and mobile applications, providing around-the-clock support from our offices in Poland, the Philippines, Mexico, and the USA. We prepare our FMCG, retail, automotive, and SaaS clients for the future by accelerating their digital transformation. Operating under the "We Code Success" principle, we prioritize the success of our clients, consultants, and partners. 

We are looking for a Fabric Data Engineer for our client from the Philippines, who helps other companies thrive in today's competitive and technology-driven world. They don't just implement systems — they enable organizations to scale efficiently.

Candidates Must Be Available to Start Immediately or Within 2 Weeks

• As a Fabric Data Engineer you will be designing, developing, and managing end-to-end ETL pipelines using Microsoft Fabric Data Factory, ensuring efficient data ingestion, cleansing, and transformation from diverse enterprise sources;
• You will be building scalable data models and implementing storage strategies in Microsoft Fabric Data Warehouse, supporting both structured and semi-structured data scenarios; 
• You will be monitoring and administering Microsoft Fabric Capacity, optimizing workloads, allocating resources effectively, and fine-tuning performance for operational reliability; 
• You will be extracting and transforming business-critical data from SAP ECC, SAP S/4HANA, and Microsoft SQL Server databases, using best practices for SAP data integration; 
• You will be collaborating with data architects, BI developers, and business stakeholders to ensure alignment of data solutions with downstream analytics and Power BI reporting needs; 
• You will be implementing robust data quality checks, validation rules, and error handling mechanisms, promoting trustworthy and governable data workflows; 
• You will be supporting the entire data lifecycle, from raw ingestion to refined datasets, ensuring consistency and traceability across pipeline executions;
• You will be producing and maintaining comprehensive technical documentation covering pipeline logic, data models, capacity configurations, and deployment standards.

• 5+ years of experience in data engineering or a closely related field, with a strong track record of delivering enterprise-level data solutions;
• Ability to work onsite at the office in Quezon City – Necessary condition;
• Availability to start immediately or within a maximum of 2 weeks – Non-negotiable requirement;
• Proficiency in Microsoft Fabric technologies: Fabric Data Factory for orchestrating ETL processes, Fabric Data Warehouse for data storage and modeling, Fabric Capacity Management for performance monitoring and optimization;
• Hands-on experience with SSIS for ETL pipelines, and SSAS for OLAP/tabular modeling; 
• Deep understanding of integrating SAP data sources, including use of CDS Views, direct table extraction, or third-party SAP connectors;
• Strong SQL development capabilities, with a focus on performance tuning and working with large volumes of data;
• Familiarity with Azure Data Platform components, such as Azure Data Lake, Azure SQL Database, and Azure Blob/Storage for modern data architecture support; 
• Solid knowledge of dimensional data modeling, including star and snowflake schemas, and best practices for analytical data structures.

• Experience integrating Power BI reports and dashboards with datasets hosted in Microsoft Fabric;
• Working knowledge of SAP Open Hub or third-party extraction tools such as Informatica or Data Services;
• Exposure to CI/CD pipelines and DevOps practices for automating deployment and monitoring of data workflows;
• Understanding of data security, compliance, and governance policies, particularly within Microsoft Azure and Fabric environments.

• Salary for work amounting to 150,000 – 185,000 PHP;
• Monthly transportation allowance of ₱4,000;
• ₱3,600 monthly de minimis non-taxable allowance;
• HMO coverage from day 1 for you and 1 dependent;
• Equipment provided;
• Optical coverage;
• Year-end leave monetization;
• Gym subscription;
• Monthly supply of coffee