Specialist – Data Integration

To develop and implement tools for data acquisition, extraction, transformation, management and manipulation of large and complex data sets to ensure data and analytics requirements are met

1.
Data Integration
Liaise with data architects to choose reference architecture and data integration styles to ensure the requirements of each data acquisition task are met
Use data acquisition, extraction, transformation, management and manipulation tools for advanced analytics in order to prepare complex data sets for data science projects
Create structured plans for the process of data transformation and integration projects to ensure requirements and timeframes are met and regular updates can be provided
Collaborate with wider IT teams in developing automation and programming scripts, refining, customising and operationalising data analytics to ensure successful deployment of analytical models
Liaise with analytics/data experts and business teams in order to define and agree the best set-up for data driven solutions Select and use appropriate data integration, analytics, visualisation and dashboard applications in order to translate business requirements into data and analytics solutions
Liaise with database administrators on data storage and delivery to ensure requirements for volume and performance are met without delays

2.
Continuous Improvement
Liaise with external data and analytics vendors to understand tools available and their application in order to keep abreast industry best practices and make recommendations for continuous improvement
Share ideas and insights from external sources with key stakeholders (wider IT and Business teams) in order to support the selection of appropriate data integration tools
Provide training and support to IT and business teams on the use of data and visualisation tools in order to raise aware and build capability across the organisation
3.
Policies, Processes, Systems and Procedures
Adhere to all relevant organisational and departmental policies, processes, standard operating procedures and instructions so that work is carried out to the required standard and in a consistent manner while delivering the required standard of service to customers and stakeholders
4.
Self-Management
Manage self in line with the bank’s people management policies, procedures, processes and practices to ensure adherence and to maximise own contribution to business performance
5.
Customer Service
Demonstrate Our Promise and apply the ADCB Service Standards to deliver the bank’s required levels of service in all internal and external customer interactions

Minimum Experience
At least 4 - 5 years of experience in data mining, large scale data acquisition, transformation and cleaning of structured and unstructured data
Minimum Qualifications
Bachelor’s Degree in a quantitative discipline such as Statistics, Mathematics, Engineering or Computer Science
Professional Qualifications
TOGAF certification or equivalent
Knowledge and Skills
Communication and persuasion skills
Understanding of architectural principles and data integration styles
Knowledge of data modelling
Familiarity with MDM, BI, and data warehouse design and implementation techniques
Knowledge of data integration tools
Job Code: 1861
Effective Date of JP: 100318
Version: 1
Experience with ETL design and implementations in the context of large datasets
SQL expertise and strong data modelling experience
Experience with Hadoop ecosystem