Data Design Expert

3 weeks ago

Rose Hill, United States Orange Full time

**votre rôle**:
As part of the End-to-End Data Quality team, the Data Design Expert will ensure through recommendations, the data journey planned is coherent from an end-to-end perspective, industrialized, relying on master data, maximizing processes and attributes reusability and ensuring the higher level of data quality natively. He will as well enforce the data quality governance and ensure his knowledge sharing.¿

Job role definition:
- On presales phase, for new Request For Proposal, he is the SPOC to analyse customer data requirements¿ and support the answer to the RFP¿
- On build phase, he can intervene on request to ensure an appropriate solution¿
- He is part of the project management team¿
- Business need identification:¿
- Collect for a new product the following information: Scope, target, deadlines, Product Opportunity assessment (number of orders, revenue estimate...) Product specificities, budget allowance, roadmap...¿
- Control if the new product will create data. How it will be exposed and to who, for what purpose.- Identify the processes and products impacted / dependant, the data domains and ensure the inclusion of the key stakeholders (SIE/SLM/GPO ) in the project- Inform the Data Regulatory compliance Officer of the new project and expose the elements collected to ensure legal constraints if any are considered¿
- New attributes¿

Each time new attributes are requested, she/he will¿
- Review and qualify the business need- Ensure the data journey planned is coherent from an end-to-end perspective, making sure if it is mandatory in a tool at end of the journey it is mandatory in the initial data source for instance¿
- Ensure format, terms and conditions for its usage are documented and reflected in the relevant processes¿
- Ensure labels are not misleading to ensure it is filled properly¿
- Data Quality governance¿
- Define data quality controls with the requestor(s) and agree the minimum data quality level expected per attribute and the business impacts if not reached to ensure the data quality governance afterwards¿
- As a preventive action, the Data Quality by Design Expert will request the support of the Customer Inventory support team to perform a data quality audit / clean-up on customer inventory, each time, we need to share inventory data with customer relying on the existing inventory (evolution platform, API for business ) This is to prevent data quality issues that could compromise the success of the new product/contract or project involving data.¿
- Dataflow architecture definition¿
- Once it is defined, she/he will control the data workflow, ensuring we rely on the right data sources to minimize the risk on Data Quality¿
- Assess the potential DQ impacts- If potential impacts are detected, he will study and qualify them and recommend alternatives to minimize the risk- TTM/ATM¿
- Once developments are done, support the test phase to validate the developments and to ensure the solution is fulfilling the required data quality score according to the KPI defined, across the different processes and for the different data consumers (reporting, customer portals ) for this solution¿
- Retrospective¿

**key accountabilities
**key result / decision areas (outcomes)
On presales phase, for new Request For Proposal, he is the SPOC to analyse customer data requirements and support the answer

Answer to the RFP with adapted solution fulfilling customer requirements and compatible with a high data quality level and with the best ROI

On build phase, on request to ensure an appropriate solution

Data solution design recommended maximize to Quality level

Collect business needs and identify dependencies and key stakeholderw

Business needs documented and key stakeholders involved in the project

Control the data workflow, ensuring we rely on the right data sources to minimize the risk on Data Quality
- and assess the potential DQ impacts ¿

Data workflow architecture recommendations done based on Data Quality assessment to limit data Quality issues exposure

Define data quality controls with the requestor(s) and agree the minimum data quality level expected per attribute and the business impacts if not reached to ensure the data quality governance afterwards ¿

User stories for new controls defined with associated business impact qualified and minimum DQ level to reach

Lessons learned documented and applied for next project

**votre profil**:
Experience:
A minimum of 3 years in data management

Good working knowledge in service provisioning process.

IT domain experience would be appreciated

Customer relationship, business acumen would be a plus

Good/Excellent technical skills on SQL

Should be an advanced user in MS Excel/Access with extended functionalities like VBA automation

Positive work attitude with ability to work well as a “team” with other teams/organizations.

Capacity to be creative and to innovate

knowledge and abilities

Ability to understand the com

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