Supply Chain Analytics Engineer

Roles & Responsibilities :

1.     Position & Objective

Design integrate and maintain logistics data pipelines and BI solutions to deliver actionable insights automate reporting and coordinate analytics & visualization initiatives with Supply chain stakeholders and Bosch plants to improve cost service and operational efficiency. 

2.     Key Responsibilities

2.1.  Data Integration & Pipeline Management

• Integrate logistics data from LSP systems internal IT platforms and Bosch plants using automated and scalable pipelines.
• Monitor pipeline health latency and failures; perform root-cause analysis and fixes.
• Manage data refresh schedules historical backfills and structural changes in source systems.

2.2.  BI Development & Automation

• Design and develop Power BI dashboards aligned with SCM KPIs operational reviews and management reporting.
• Automate data refreshes alerts and report distributions using Power Automate and Python.
• Optimize data models DAX calculations and performance for large logistics datasets.

2.3.  Insight Generation & Decision Support

• Translate analytical findings into clear actionable recommendations for SCM leadership.
• Support network optimization initiatives such as milk runs rental models and round-trip analysis.

2.4.  Data Governance & Quality Monitoring

• Define and enforce data standards master data definitions and KPI logic across reports.
• Implement data quality checks reconciliation controls and audit trails for logistics data.
• Document data flows transformations and assumptions to ensure transparency and continuity.

Qualifications :

Requirements & Qualifications

Educational Qualifications

• Bachelors degree (B.E. /) in Computer Science Data Analytics Information Systems or related engineering disciplines.
• Specialization or coursework in Supply Chain Management Logistics or Operations Analytics is preferred.
• Equivalent professional certifications or relevant industry experience may be considered in lieu of specialization.

Professional Qualifications & Skills

Technical & Platform Skills

• SQL: Strong working knowledge of SQL for data extraction transformation and performance-optimized querying.
• Python: Proficiency in Python for data processing automation and analytics; working knowledge of R is an advantage.
• Power Platform: Hands-on experience with Microsoft Power Platform including Power BI and Power Automate.
• APIs: Experience integrating data via APIs including data ingestion validation and error handling.

Data Engineering & Cloud

• Understanding of data standards data modeling and master data concepts in enterprise environments.
• Experience with cloud data platforms such as Microsoft Azure and Snowflake for analytics workloads.
• Familiarity with data pipelines storage layers and secure access management.

Analytics & Digitalization

• Strong analytical thinking ability to translate business and supply chain problems into scalable analytical solutions.

Communication & Collaboration

• Strong communication skills to engage effectively with SCM teams Internal IT Bosch plants and LSP partners.
• Ability to explain technical concepts clearly to non-technical stakeholders.
• Proven capability to work collaboratively in cross-functional multi-stakeholder environments.

Mindset & Ownership

• High level of initiative with an innovative problem-solving mindset. Willingness to challenge manual processes and drive automation-first thinking.
• Strong sense of ownership accountability and continuous improvement.

Remote Work :

No

Employment Type :

Full-time