Define and maintain data models for financial reporting data on Google Cloud Platform and BigQuery currently provided through SAP BW.
Model financial reporting data across key business dimensions such as account, entity, store, period, reporting scenario, currency, KPI and reporting hierarchy.
Design scalable, secure, and cost-efficient data warehouse solutions supporting financial reporting and analytics use cases.
Design reporting-ready data layers that support standard reports, dashboards, flexible analysis and reconciliation with existing SAP BW outputs.
Establish data integration, ingestion, transformation, and storage standards for SAP, Tagetik and other finance-related data sources.
Design and implement ELT/ETL frameworks, data pipelines, and reusable data engineering patterns.
Optimize BigQuery performance, data partitioning, clustering, and workload management.
Define and implement monitoring, data quality, and operational support processes.
SAP BW Modernization:
Collaborate with business and technical teams to migrate reporting and analytical logic from SAP BW 7.5 to BigQuery.
Translate existing BW data models, transformations, and financial reporting business logic into scalable SQL-based cloud solutions.
Support migration of financial reporting capabilities including KPI structures, reporting hierarchies, financial calculations, currency-related logic and reporting-ready data views.
Support the implementation of SAP ECC, SAP BW, Tagetik and other finance-related ingestion patterns into BigQuery.
Contribute to migration planning, solution design, testing, and deployment activities.
Identify opportunities to simplify legacy architectures and improve data accessibility.
Analytics & Reporting:
Design and implement enterprise reporting solutions using MicroStrategy.
Develop and maintain MicroStrategy schemas, attributes, metrics, facts, intelligent cubes, reports, dashboards, and dossiers.
Design semantic layers and reporting-ready data models to support self-service analytics.
Partner with business stakeholders to translate reporting and KPI requirements into scalable analytical solutions.
Ensure financial reporting requirements are accurately reflected in reporting models and reporting outputs.
Ensure report accuracy, usability, performance.
Stakeholder Management & Collaboration
Act as the technical lead for financial reporting data models and analytics solutions on BigQuery and MicroStrategy.
Collaborate with business, IT, SAP, and cloud stakeholders to ensure successful project delivery.
Support future innovation initiatives including advanced analytics, AI, and machine learning use cases.
Professional Experience
Minimum 5 years of experience in Data Engineering, Data Warehousing, or Analytics Engineering.
Minimum 3 years of hands-on experience with Google Cloud Platform and BigQuery.
Experience working with financial reporting, controlling, planning, consolidation or management reporting solutions
Proven experience designing and implementing enterprise-scale cloud data warehouse and analytics solutions.
Experience delivering end-to-end data warehouse modernization or migration projects.
Experience working with SAP data sources, preferably SAP ECC, SAP BW, SAP S/4HANA or Tagetik Consolidation.
Strong experience developing enterprise reporting solutions using MicroStrategy.
Technical Skills
Google Cloud & BigQuery
Google Cloud Platform (GCP)
BigQuery architecture and administration
Data warehouse design and optimization
Cloud security and IAM
Data lifecycle management
Performance tuning and cost optimization
Data Engineering
Design of reporting-ready data models and semantic layers
Handling of hierarchies, master data and reporting structures
Advanced SQL
ETL/ELT architecture and implementation
Data modeling (Star Schema, Snowflake Schema, Data Vault knowledge desirable)
Data quality and reconciliation frameworks
Data integration and replication concepts
Python or comparable programming languages
Git and CI/CD pipelines
Business Intelligence & Analytics
MicroStrategy Architecture
MicroStrategy Dashboard and Report Development
Semantic Layer Design
KPI and Metric Modeling
Analytics and Data Visualization Best Practices
Preferred Qualifications
Experience with SAP BW-to-cloud migration initiatives.
Experience with Tagetik or comparable consolidation and performance management solutions
Experience with group reporting, management reporting or controlling processes
Knowledge of Google Cortex Framework.
Experience with modern analytics platforms such as Looker, Power BI, or Tableau.
Understanding of AI/ML-enabled data platforms and advanced analytics architectures.
Experience working in large-scale retail, wholesale, or consumer goods organizations.
Personal Competencies
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management capabilities.
Ability to translate business requirements into technical solutions.
Self-driven, pragmatic, and results-oriented mindset.
Strong collaboration skills in cross-functional and international environments.
Ability to lead technical discussions and influence architectural decisions.
Key Requirements & Skills
Minimum 5 years of experience in Data Engineering, Data Warehousing, or Analytics Engineering
Minimum 3 years of hands-on experience with Google Cloud Platform and BigQuery
Experience working with financial reporting, controlling, planning, consolidation, or management reporting solutions
Proven experience designing and implementing enterprise-scale cloud data warehouse and analytics solutions
Experience delivering end-to-end data warehouse modernization or migration projects
Experience working with SAP data sources, preferably SAP ECC, SAP BW, SAP S/4HANA, or Tagetik Consolidation
Strong experience developing enterprise reporting solutions using MicroStrategy
Experience with SAP BW-to-cloud migration initiatives
Experience with Tagetik or comparable consolidation and performance management solutions
Experience with group reporting, management reporting, or controlling processes
Knowledge of Google Cortex Framework
Experience with modern analytics platforms such as Looker, Power BI, or Tableau
Understanding of AI/ML-enabled data platforms and advanced analytics architectures
Experience working in large-scale retail, wholesale, or consumer goods organizations
Frequently Asked Questions
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Salary details will be discussed during the interview.
