
We are looking for an experienced BI Solution Architect to lead the design and implementation of scalable, secure, and high-performing Data & BI platforms across Azure and GCP environments.
This role will own the end-to-end data architecture covering ingestion, storage, processing, transformation, analytics, and visualization while driving enterprise BI strategy, reporting governance, and modernization initiatives. The ideal candidate will work closely with business stakeholders, enterprise architects, and engineering teams to deliver robust, production-ready analytics solutions.
Key Responsibilities:
Data Architecture & Solution Design
- Define architecture for data ingestion, storage, processing, and transformation across Azure and GCP.
- Design scalable, resilient, and enterprise-grade data platforms aligned with architectural standards.
- Create data models, architecture blueprints, and end-to-end data flow designs.
- Collaborate with enterprise architects to ensure architectural compliance and governance.
Data Platform & Pipeline Architecture
- Design and oversee large-scale distributed data platforms and pipelines.
- Define standards for data ingestion, transformation, and consumption layers.
- Enable development of scalable and reusable data products.
- Promote modern data architectures including:
- Data Lake
- Lakehouse
- Data Mesh
BI Strategy & Architecture
- Define and drive enterprise BI strategy aligned with business objectives.
- Standardize BI architecture and reporting frameworks across the organization.
- Evaluate and recommend BI technologies including:
- Power BI
- Tableau
- SAP Business Objects (BO)
- Develop reusable blueprints, patterns, and accelerators.
- Lead proof-of-concepts (POCs) and BI modernization initiatives.
Visualization Governance
- Establish dashboard development standards and visualization best practices.
- Define governance frameworks to improve dashboard quality, consistency, and usability.
- Review dashboards prior to production deployment.
- Guide teams in creating intuitive, business-focused, and high-performance visualizations.
Data Governance & Enterprise Data Management
- Define and enforce enterprise data governance standards.
- Drive metadata management, master data management, and reference data practices.
- Establish data quality frameworks, validation mechanisms, and monitoring processes.
- Create technical glossaries and enterprise-wide data standards.
Security & Compliance
- Define access management and security standards across Data & BI platforms.
- Implement controls for sensitive and regulated data.
- Ensure compliance with enterprise policies and regulatory requirements.
Performance & Optimization
- Define monitoring, tuning, and optimization strategies for data pipelines and dashboards.
- Ensure scalability, responsiveness, and reliability of analytics platforms.
- Implement proactive monitoring and observability frameworks.
Leadership & Stakeholder Management
- Partner with Product Owners, Business Analysts, and stakeholders to translate requirements into architecture solutions.
- Collaborate with Data Engineers, Analysts, and Data Scientists to solve complex technical challenges.
- Mentor engineers and associate architects.
- Lead architecture reviews and drive solution governance.
Data Lifecycle & Operations
- Own end-to-end data lifecycle management:
- Ingestion
- Processing
- Storage
- Archival
- Ensure operational readiness and reliability of critical data platforms.
- Drive best practices around scalability, resilience, and sustainability.
Migration & Modernization
- Lead Tableau-to-Power BI migration strategy and execution.
- Design dual-platform architectures to ensure business continuity during migration.
- Drive legacy platform rationalization and modernization initiatives.
- Optimize infrastructure and licensing costs while reducing total cost of ownership (TCO).
Required Qualifications
Experience
- 8+ years of experience in Data Engineering, Big Data, Analytics, or Data Architecture.
- Proven experience designing enterprise-scale data platforms and analytics solutions.
- Strong stakeholder management and leadership experience.
Technical Expertise
- Strong expertise in Azure and GCP data ecosystems.
- Deep understanding of:
- Data Modeling
- ETL / ELT
- Distributed Systems
- Enterprise Data Platforms
- Experience with modern architectures:
- Data Lake
- Lakehouse
- Data Mesh
BI & Analytics
- Strong hands-on experience with:
- Power BI
- Tableau
- SAP Business Objects (BO)
- Expertise in:
- BI Architecture
- Dashboard Design
- Visualization Best Practices
- Reporting Governance
Data Governance
- Strong understanding of:
- Data Governance
- Data Quality
- Metadata Management
- Data Lifecycle Management
Must-Have Skills
- Data Architecture & Solution Design (Azure & GCP)
- Large-Scale Data Platform & Pipeline Design
- Data Modeling & ETL/ELT Architecture
- Distributed Systems
- Data Lake / Lakehouse / Data Mesh
- Power BI & Tableau
- Data Governance & Data Quality
- Enterprise BI Architecture
- Stakeholder Management & Leadership
Good-to-Have Skills
- Enterprise Data Platforms & Multi-Cloud Environments
- CI/CD Pipelines & Automation for Data & BI Platforms
- Real-Time / Streaming Data Architectures
- BI Transformation & Modernization Programs
- Tableau to Power BI Migration Experience
- Azure Data Engineer / Architect Certifications
- GCP Professional Data Engineer / Cloud Architect Certifications
Why Join Us?
- Lead architecture for enterprise-scale Data & BI platforms.
- Drive organization-wide data and analytics strategy.
- Work on modern cloud ecosystems across Azure and GCP.
- High ownership, visibility, and stakeholder exposure.
- Opportunity to shape long-term data, analytics, and visualization roadmaps.

About Quantiphi
About
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to reimagine and realize transformational opportunities at the heart of the business. Since its inception in 2013, Quantiphi has solved the toughest and most complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve accelerated and quantifiable business results.
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