Bosch

Company Description

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 Description

Roles & 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.

Qualifications

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 :

Additional Information