Data Engineer
Summary
Designs and builds scalable Microsoft Fabric-based data pipelines and warehouses for analytics, using Azure, Python, and Spark to support banking or telecom reporting needs.
Systems Limited APAC is hiring data engineers to design, build, and maintain scalable data pipelines and infrastructure that support analytics, reporting, and business intelligence initiatives.
Responsibilities:
- Lead end-to-end solution architecture and design for Microsoft Fabric-based data platforms.
- Design scalable and high-performance cloud data architectures aligned with business requirements.
- Develop and maintain enterprise data models (conceptual, logical, and physical) to support analytics and reporting.
- Architect and implement modern data engineering solutions using Microsoft Fabric, OneLake, Data Factory, Spark, and Data Warehouses.
- Design and optimize data ingestion, transformation, integration, and orchestration pipelines.
- Architect real-time and streaming data solutions using Eventstreams, KQL databases, Spark Structured Streaming, and other Microsoft Fabric streaming capabilities.
- Collaborate with business stakeholders, solution architects, and engineering teams to translate business needs into technical solutions.
- Optimize platform performance, scalability, reliability, and cost efficiency.
- Provide technical leadership, architecture reviews, and mentorship to data engineers and developers.
- Define architecture standards, reference patterns, and implementation roadmaps.
- Stay current with Microsoft Fabric, Azure Data Platform, and industry best practices to drive continuous innovation.
Requirements:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 4+ years of experience in Data Engineering specifically in Banking or Telecom (Telco) domains.
- Strong hands-on experience in Azure, AWS and Snowflake.
- Programming knowledge in Python, Scala, or Java.
- Experience in building ETL/ELT pipelines.
- Good understanding of data warehousing and dimensional modelling.
- Exposure to Microsoft Dynamics 365 (D365) data platforms.
- Experience with Azure Synapse Link or Microsoft Fabric Link.
- Knowledge of Spark, Kafka, or other big data technologies.
- Familiarity with orchestration tools (Airflow, ADF).