About the role
Responsible for developing, optimize, and maintaining business intelligence and data warehouse systems, ensuring secure, efficient data storage and retrieval, enabling self-service data exploration, and supporting stakeholders with insightful reporting and analysis.
Grade - T5
Please note that the Job will close at 12am on Posting Close date, so please submit your application prior to the Close Date
What your main responsibilities are
Accountabilities:
• Data Pipeline - Develop and maintain scalable data pipelines and builds out new API integrations to
support continuing increases in data volume and complexity
• Data Integration - Connect offline and online data to continuously improve overall understanding of
customer behavior and journeys for personalization. Data pre-processing including collecting, parsing,
managing, analyzing and visualizing large sets of data
• Data Quality Management - Cleanse the data and improve data quality and readiness for analysis.
Drive standards, define and implement/improve data governance strategies and enforce best practices
to scale data analysis across platforms
• Data Transformation - Processes data by cleansing data and transforming them to proper storage
structure for the purpose of querying and analysis using ETL and ELT process
• Data Enablement - Ensure data is accessible and useable to wider enterprise to enable a deeper and
more timely understanding of operation.
Qualifications & Specifications:
• Masters /Bachelor’s degree in Engineering /Computer Science/ Math/ Statistics or equivalent.
• Strong programming skills in Python/Pyspark/SAS.
• Proven experience with large data sets and related technologies – Hadoop, Hive, Distributed
computing systems, Spark optimization.
• Experience on cloud platforms (preferably Azure) and it's services Azure Data Factory (ADF), ADLS
Storage, Azure DevOps. Hands-on experience on Databricks, Delta Lake, Workflows.
• Should have knowledge of DevOps process and tools like Docker, CI/CD, Kubernetes, Terraform,
Octopus.
• Hands-on experience with SQL and data modeling to support the organization's data storage and
analysis needs.
• Proficiency in enterprise data pipeline and ETL tools…
