Expert in architect, design,construct, install, test and maintain highly scalable and optimizeddata pipelines with state-of-the-art monitoring and establishedbaseline pipeline architecture.
Architect, build theoptimal data extraction & transformation mechanisms forvarious kinds of data, optimal technology for storing data in thedata lake;
based on size, complexity and needs from business teams
Architect the solution to ensure optimal maintenanceprocess for the data in the lake; in terms of real time needs; dataanalysis needs and data archiving / long term data retention.
Bring together large, complex and sparse data sets tomeet functional and non-functional business requirements and use avariety of languages, tools and frameworks to marry data
Design and implement data tools for analytics and data scientistteam members to help them in building, optimizing and tuning of usecases.
Architect, design and build data warehousesolutions.
Establish the data access guidelines coveringdata cataloguing, data semantics, data security, data governancewhere needed.
Provide technical leadership to the dataengineering team and review / contribute to the artefactsdelivered, including technical architecture, functional andnon-functional requirements, interface specifications and highlevel design documents.
Proficient in architecturalpatterns and ensure to QR-IT Software Governance Integrationstandards.
Lead root cause analysis of reported criticalincidents and recommend / ensure implementation of effectivepreventive actions to avoid repetition.
Reviewfunctional and non-functional requirements for the deliveriesassigned and recommend / develop technology frameworks.
Drive high performance and accountability for superior results andemployee engagement. Provide staff with timely, candid andconstructive performance feedback;
develop employees to theirfullest potential and provide challenging opportunities thatenhance employee career growth; recognize and reward employees foraccomplishments.
Promote, train, support, and advocateData Architecture best practices, such as, master data management,data modeling, data modernization etc.
Establish thedepartment or teams objectives and priorities to align with andsupport business objectives.
Regularly evaluate thedepartment or team objectives, plans, procedures, practices, andmakes appropriate changes if needed.
Recruit, train anddevelop team members to create a high quality data engineeringcapability