Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 28,200+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.
Job DescriptionRoles & Responsibilities :
Data Quality, Modelling & Root Cause Analysis
Utilize deep expertise in SAP MDG/ECCs and Azure Data Lake (via Databricks) using SQL/Python to perform root cause analysis on assigned data quality use cases.
Develop and refine both conceptual and physical data models to automate monitoring of ongoing data quality issues. Facilitate multiple workshops to explore and select the most effective modelling options.
Collaborate with business stakeholders (Data Owners and Data Stewards) to profile data, identify quality issue patterns, and assess impacts on critical data elements (CDEs) relevant to each business area.
Quantify financial impacts of data quality issues and articulate both quantitative and qualitative business benefits of remediation efforts, managing implementation timelines effectively.
Schedule and lead regular working groups with business units to drive progress on root cause analysis (RCA), remediation actions, or to prepare issues for discussion in Data Governance Forums (DGFs).
Define business data quality rules that form the basis for KPIs and measures, feeding into dashboards and workflows for continuous monitoring and timely issue escalation.
Maintain comprehensive understanding of the data quality value chain, including CDE concepts, issue management, KPIs, and governance. Lead execution of data quality assessments to support process improvements and BAU initiatives.
Proactively identify hidden or emerging data quality risks and escalate to Lead/Manager as necessary.
Communicate clearly and effectively, articulating complex data quality issues and their business implications to diverse, outward-facing audiences.
Dashboarding & Workflow Management
Support the design, development, and deployment of data quality dashboards using Power BI to provide clear visibility into data health and trends.
Establish escalation protocols and construct workflows with alerts that notify process and data owners about unresolved data quality issues, ensuring timely resolution.
Collaborate with IT and analytics teams to incorporate advanced technologies such as AI, Machine Learning, and cognitive science to innovate data quality processes.
Data Quality Improvement Plans
Partner with business functions and projects to create and embed actionable data quality improvement plans, fostering accountability and business ownership.
Set clear targets for data quality maturity and monitor progress, intervening proactively when improvements lag expectations.
Support ongoing initiatives focused on cleaning and enhancing the existing data landscape.
Project Delivery & Governance Support
Lead and direct Data Quality Analysts in executing profiling, establishing conversion criteria, and resolving complex data quality issues from both technical and business perspectives.
Own and produce data quality deliverables aligned with DAS data change methodology and ensure data quality is integrated into Gold and Silver level data change projects.
Contribute insights to the development of business cases by quantifying the cost of poor data and the benefits of remediation.
Educational qualification:
B.E
Experience :
7 to 11 years of relevant experience in the Oil & Gas or Financial Services/Banking industries within the Data Management domain.
Proven expertise in designing, developing, and fine-tuning data models and data structures.
Hands-on experience with Data Quality Management practices including governance, data quality issue identification and remediation, forum facilitation, critical data element (CDE) identification, and data lineage documentation.
Experience in handling data quality KPIs, measures, and continuous improvement frameworks.
Demonstrated ability to engage and influence senior stakeholders across multiple data domains, Chief Data Office (CDO), and technology teams in a global, multi-time zone environment.
Ability to operate in dynamic, rapidly changing setups with minimal supervision; able to prioritize and deliver independently.
Mandatory/requires Skills :
Preferred Skills :
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