Sr. Data Engineer

We are seeking a highly skilled Senior Data Engineer to lead the design, development, and deployment of data pipelines for a Microsoft Fabric-based data lakehouse implementation at a prominent Philippine water utility company . In this role, you will build and maintain scalable and efficient data pipelines, ingesting and transforming large datasets from various sources, such as billing systems (SAP IS-U) , SCADA , IoT sensors , customer service data , and more.

As a Senior Data Engineer , you will collaborate with data architects, business analysts, data scientists, and the wider IT team to ensure that the lakehouse solution is optimized, secure, and meets regulatory and business needs. You will have the opportunity to mentor junior engineers, drive best practices, and contribute to the overall cloud architecture strategy.

• Lead the development and maintenance of cloud-based data pipelines on Microsoft Fabric , ensuring that data from operational systems (e.g., SAP IS-U , SCADA , IoT sensors ) is ingested, transformed, and loaded into the lakehouse in an optimized and scalable way.
• Collaborate with stakeholders to define and implement best practices for data architecture, ensuring the solution is scalable, cost-effective, and performant.
• Design and implement ETL/ELT pipelines to handle large-scale data loads, ensuring high data quality and consistency across the data lakehouse environment.
• Ensure data security , compliance , and privacy standards are met, especially in line with Philippine regulations (e.g., Data Privacy Act , MWSS , LWUA ) for data handling within the water utility sector.
• Lead the integration of SAP IS-U , SCADA , and other operational data sources into the Microsoft Fabric data lakehouse using Azure Data Factory , Azure Synapse Analytics , and related tools.
• Optimize data storage and retrieval performance in the lakehouse using Azure Data Lake , Azure Synapse , and Microsoft Fabric while ensuring a balance between cost, performance, and scalability.
• Work with data scientists and business analysts to ensure the data lakehouse meets reporting and analytical requirements (e.g., Power BI integration, regulatory reporting).
• Mentor and provide technical guidance to junior data engineers , ensuring code quality and best practices in development, deployment, and maintenance of data pipelines.
• Automate and optimize data processing workflows using Azure DevOps , CI/CD pipelines , and infrastructure-as-code practices (e.g., Terraform , ARM Templates ).
• Troubleshoot and resolve complex data pipeline issues, including performance bottlenecks, data inconsistencies, and integration problems.
• Stay up-to-date with cloud technologies , data engineering trends , and Microsoft Fabric features to continuously improve data engineering practices.

• Bachelor’s degree in Computer Science , Information Systems , Engineering , or a related field.
• 7+ years of experience in data engineering , with at least 3–5 years focused on cloud-based data platforms and Microsoft Azure .
• In-depth experience with ETL/ELT tools and frameworks, including SSIS/SSAS , Azure Databricks , and Python
• Proven track record of building scalable data pipelines and implementing data integration solutions for large datasets in cloud environments.
• Familiarity with SAP IS-U , SCADA , and IoT data sources, or knowledge of operational data in the water utilities sector.
• Experience in implementing data security , governance , and privacy controls in line with industry standards and regulations.
• Strong knowledge of cloud infrastructure optimization , including cost management and resource scalability in Microsoft Azure.
• Expertise in data modeling , data transformation , and data pipeline orchestration .
• Hands-on experience with DevOps tools like Azure DevOps , Git , and CI/CD for automating deployment and monitoring.

• Experience in water utilities , energy , or other regulated sectors .
• Familiarity with data lakehouse architectures and frameworks (e.g., Delta Lake ).
• Experience with Python , Spark , or other distributed data processing frameworks .
• Familiarity with data privacy laws in the Philippines, such as the Data Privacy Act , and utility-sector regulations (e.g., MWSS , LWUA ).
• Experience in machine learning or AI integrations within a data lakehouse architecture for advanced analytics.
• Strong experience in SSIS and SSAS
• Leadership and mentoring skills, with the ability to guide junior engineers and foster a collaborative team environment.
• Excellent communication skills , with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Strong problem-solving and troubleshooting skills, with the ability to manage and resolve complex data engineering challenges.
• Highly organized, self-motivated, and able to work independently while managing multiple tasks and priorities.
• Adaptable and eager to stay current with emerging cloud technologies, especially in the context of data engineering and cloud-native solutions.

Thakral One is a consulting and technology services company headquartered in Singapore, with a pan-Asian presence. We focus primarily around technology-driven consulting, adoption of value-added bespoke solutions, enabling enhanced decision support through data analytics, and embracing possibilities in the cloud. We are heavily inclined towards building capabilities collaboratively with clients and believe strongly in improving grounded and practical outcomes. This approach is possible through our partnership with leading global technology providers and internal R&D teams. Our clients come from Financial Services, Banking, Telco, Government, Healthcare, and Consumer-oriented organisations.