Data Quality(DQ) Specialist

JOB RESPONSIBILITIES:

The job entails you to work with our clients and partners to design, define, implement, roll-out, and

improve Data Quality that leverage various tools available in the market for example: Informatica IDQ or SAP DQ or SAP MDG or Collibra DQ or Talend DQ or Custom DQ Solution and/or other leading platform for the client’s business benefit. The ideal candidate will be responsible for ensuring the accuracy, completeness, consistency, and reliability of data across systems. You will work closely with data engineers, analysts, and business stakeholders to define and implement data quality frameworks and tools. As part of your role and responsibilities, you will get the opportunity to be involved in the entire business development life-cycle:

 Meet with business individuals to gather information and analyze existing business processes,

determine and document gaps and areas for improvement, prepare requirements documents,

functional design documents, etc. To summarize, work with the project stakeholders to identify

business needs and gather requirements for the following areas: Data Quality and/or Data

Governance or Master Data

 Follow up of the implementation by conducting training sessions, planning and executing

technical and functional transition to support team.

 Ability to grasp business and technical concepts and transform them into creative, lean, and

smart data management solutions.

 Development and implementation of Data Quality solution in any of the above leading

platform-based Enterprise Data Management Solutions

o Assess and improve data quality across multiple systems and domains.

o Define and implement data quality rules, metrics, and dashboards.

o Perform data profiling, cleansing, and validation using industry-standard tools.

o Collaborate with data stewards and business units to resolve data issues.

o Develop and maintain data quality documentation and standards.

o Support data governance initiatives and master data management (MDM).

o Recommend and implement data quality tools and automation strategies.

o Conduct root cause analysis of data quality issues and propose remediation plans.

o Implement/Take advantage of AI to improve/automate Data Quality solution

o Leveraging SAP MDG/ECCs experience the candidate is able to deep dive to do root cause analysis for assigned usecases. Also able to work with Azure data lake (via

dataBricks) using SQL/Python.

o Data Model (Conceptual and Physical) will be needed to be identified and built that

provides automated mechanism to monitor on going DQ issues. Multiple workshops

may also be needed to work through various options and identifying the one that is

most efficient and effective

o Works with business (Data Owners/Data Stewards) to profile data for exposing patterns

indicating data quality issues. Also is able to identify impact to specific CDEs deemed

important for each individual business.

o Identifies financial impacts of Data Quality Issue. Also is able to identify business benefit

(quantitative/qualitative) from a remediation standpoint along with managing

implementation timelines.

o Schedules regular working groups with business that have identified DQ issues and

ensures progression for RCA/Remediation or for presenting in DGFs

o Identifies business DQ rules basis which KPIs/Measures are stood up that feed into the

dashboarding/workflows for BAU monitoring. Red flags are raised and investigated

o Understanding of Data Quality value chain, starting with Critical Data Element concepts,

Data Quality Issues, Data Quality KPIs/Measures is needed. Also has experience owing

and executing Data Quality Issue assessments to aid improvements to operational

process and BAU initiatives

o Highlights risk/hidden DQ issues to Lead/Manager for further guidance/escalation

o Communication skills are important in this role as this is outward facing and focus has to

be on clearly articulation messages.

o Support designing, building and deployment of data quality dashboards via PowerBI

o Determines escalation paths and constructs workflow and alerts which notify process

and data owners of unresolved data quality issues

o Collaborates with IT & analytics teams to drive innovation (AI, ML, cognitive science etc.)

o Works with business functions and projects to create data quality improvement plans

o Sets targets for data improvements / maturity. Monitors and intervenes when sufficient

progress is not being made

o Supports initiatives which are driving data clean-up of existing data landscape

JOB REQUIREMENTS:

i. Education or Certifications:

 Bachelor's / Master's degree in engineering/technology/other related degrees.

 Relevant Professional level certifications from Informatica or SAP or Collibra or Talend or any

other leading platform/tools

 Relevant certifications from DAMA, EDM Council and CMMI-DMM will be a bonus

ii. Work Experience:

 You have 4-10 years of relevant experience within the Data & Analytics area with major

experience around data management areas: ideally in Data Quality (DQ) and/or Data

Governance or Master Data using relevant tools

 You have an in-depth knowledge of Data Quality and Data Governance concepts, approaches,

methodologies and tools

 Client-facing Consulting experience will be considered a plus

iii. Technical and Functional Skills:

 Hands-on experience in any of the above DQ tools in the area of enterprise Data Management

preferably in complex and diverse systems environments

 Exposure to concepts of data quality – data lifecycle, data profiling, data quality remediation(cleansing, parsing, standardization, enrichment using 3 rd party plugins etc.) etc.

 Strong understanding of data quality best practices, concepts, data quality management

frameworks and data quality dimensions/KPIs

 Deep knowledge on SQL and stored procedure

 Should have strong knowledge on Master Data, Data Governance, Data Security

 Prefer to have domain knowledge on SAP Finance modules

 Good to have hands on experience on AI use cases on Data Quality or Data Management areas

 Prefer to have the concepts and hands on experience of master data management – matching,

merging, creation of golden records for master data entities

 Strong soft skills like inter-personal, team and communication skills (both verbal and written)