Senior data engineer in Singapore who builds and maintains scalable ETL pipelines in Databricks, writes optimized SQL, automates dashboards in Power BI/Tableau/Looker, and ensures data quality on Azure or AWS, working closely with analysts and business stakeholders.
Build and maintain scalable ETL pipelines in Databricks to process and transform large datasets from multiple sources.
Write optimized SQL queries to prepare datasets for analytics and reporting.
Collaborate with analysts and business stakeholders to understand reporting needs and translate them into technical solutions.
Develop and automate analytics reports and dashboards using tools like Power BI, Tableau, or Looker.
Implement data quality checks and monitoring to ensure accuracy and reliability.
Optimize data models for performance and scalability in a cloud-based environment (e.g., Azure, AWS).
Document data flows, transformations, and reporting logic for transparency and maintainability.
Added advantage if they have Print domain experience
Certification
Any degree or equivalent.
About Mphasis
Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis' Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis' Service Transformation approach helps 'shrink the core' through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis' core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.