Senior Quality Assurance Specialist

ABOUT THE ROLE You will be part of a Global Data Office team, responsible for driving data quality across enterprise SAP systems. The role involves building DQ rules and dashboards, conducting root cause analysis, and embedding continuous monitoring frameworks across global data platforms . Role : Senior Data Quality Assurance Analy stEngagement : Contract 6 Months (Possibility of Extensio n)Work Mode : Hybrid - Chenn aiIndustry : Pharmaceutical / Global Enterprises KEY RESPONSIBILITIES Develop Data Quality rules using SQL, Acceldata, Experian Aperture, or similar DQ tools Build and maintain self-serve Data Quality dashboards in Power BI using Snowflake as the data so urce Conduct in-depth data profiling, analysis, and root cause analysis (RCA) across critical data objects Automate data quality monitoring processes and drive AI/ML use cases for DQ improvement Manage DQ incidents and embed continuous monitoring mechanisms Collaborate with data stewards, business owners, and IT teams to define DQ KPIs and governance standards Train and coach data owners and stewards in managing data quality. MUST-HAVE SKILLS Hands-on expertise in Power BI for DQ dashboards and reporting Strong proficiency in Snowflake / T-SQL / Snowflake SQL Experience with Power Platform (Power Automate, Power Apps, Dataflows) Exposure to at least one DQ tool: Acceldata, Experian Aperture, Ataccama, Alteryx, Trillium, or SAS Viya Strong ETL automation and data reconciliation background Solid understanding of Data Quality, Data Governance, and Data Architecture frameworks Experience using AI Agents / Copilot for DQ automation Excellent data profiling, analysis, and stakeholder communication skills Prior experience working in a global organisation (pharma preferred) GOOD TO HAVE Experience with SAP MDG / ECC / S/4 HANA data environments Familiarity with data lineage/governance tools like Collibra or Talend Knowledge of data cleansing tools (Winshuttle, Aperture) Exposure to data observability with AI pattern detection Experience in lean/agile environments with data governance methodologies ABOUT THE ROLE You will be part of a Global Data Office team, responsible for driving data quality across enterprise SAP systems. The role involves building DQ rules and dashboards, conducting root cause analysis, and embedding continuous monitoring frameworks across global data platforms . Role : Senior Data Quality Assurance Analy stEngagement : Contract 6 Months (Possibility of Extensio n)Work Mode : Hybrid - Chenn aiIndustry : Pharmaceutical / Global Enterprises KEY RESPONSIBILITIES Develop Data Quality rules using SQL, Acceldata, Experian Aperture, or similar DQ tools Build and maintain self-serve Data Quality dashboards in Power BI using Snowflake as the data so urce Conduct in-depth data profiling, analysis, and root cause analysis (RCA) across critical data objects Automate data quality monitoring processes and drive AI/ML use cases for DQ improvement Manage DQ incidents and embed continuous monitoring mechanisms Collaborate with data stewards, business owners, and IT teams to define DQ KPIs and governance standards Train and coach data owners and stewards in managing data quality. MUST-HAVE SKILLS Hands-on expertise in Power BI for DQ dashboards and reporting Strong proficiency in Snowflake / T-SQL / Snowflake SQL Experience with Power Platform (Power Automate, Power Apps, Dataflows) Exposure to at least one DQ tool: Acceldata, Experian Aperture, Ataccama, Alteryx, Trillium, or SAS Viya Strong ETL automation and data reconciliation background Solid understanding of Data Quality, Data Governance, and Data Architecture frameworks Experience using AI Agents / Copilot for DQ automation Excellent data profiling, analysis, and stakeholder communication skills Prior experience working in a global organisation (pharma preferred) GOOD TO HAVE Experience with SAP MDG / ECC / S/4 HANA data environments Familiarity with data lineage/governance tools like Collibra or Talend Knowledge of data cleansing tools (Winshuttle, Aperture) Exposure to data observability with AI pattern detection Experience in lean/agile environments with data governance methodologies