Oversee the design, development, and maintenance of ETL processes, ensuring they meet business requirements
Lead the team of data engineers perform data cleaning, preparation, reporting, and data analysis
Oversee the process of data extraction, aggregation, and quality checking from multiple sources and tables in support of trend identification, root cause analysis, and validation of the performance measures
Lead development and maintenance of a data pipeline and data warehouse
Lead troubleshooting data pipeline and data warehouse issues
Create and maintain optimal data pipeline architecture
Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it
Design data integrations and data quality framework
Define, develop and implement high level cutover strategy and rehearsal/cutover plans within multiple overlapping data migration events
Identify, assess, and manage potential risks associated with migration implementation activities and develop mitigation plans to minimise impact
Contribute to the development of the technical cutover schedules to ensure they align to larger cutover plans and meet business objectives
Coordinating development/deployment team members to support and facilitate Dress Rehearsals
Planning and coordination of post implementation Warranty/Hypercare if applicable
Develop and implement a technical release plan, including schedule, risks, dependencies, and resource requirements for DEV/ TEST/ SIT/ Pre Prod/ Prod environments for each Release supported by multiple development teams
Monitor progress of development, manage code release packaging, versioning, maintenance and deployment activities against the technical release plan, and consider alignment to broader project timelines and project plans scope, schedules, budgets, risks, resources, and quality.
Qualifications:
Graduate of BS Mathematics, Computer Science, Information Management, Information Technology, Statistics or related courses
Has at least five (5) years of experience in data engineering in a customer or business facing capacity
A strong understanding of data modelling, data structures, databases, and ETL processes
Strong technical understanding of Data Analytics concepts, data warehouses and marts reporting and visualizations
Experience using data extraction and analysis tools, such as SQL and Python
Technical expertise regarding data models, database design, ETL development, and data mining
With skills in predictive modeling
General understanding of ETL/ELT frameworks, error handling techniques, data quality techniques and their overall operation
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
Possess excellent oral and written communication and interpersonal skills
A plus if with at least one year experience in Power BI
