Description : Seeking a senior Data Architect (10+ years experience) to design and deliver scalable data and analytics solutions across cloud and enterprise platforms. This role requires deep expertise in data modeling, pipelines, BI frameworks, and cloud-native architectures (Azure & GCP), with a strong background in integrating enterprise business systems.

Detailed Overview :

Role Summary : Architect - Data & Analytics

1. Functional Knowledge :

The Architect will possess a deep understanding of core master data domains and key business applications, including Salesforce (CRM), Dynamics (ERP) and Oracle E-Business Suite (ERP), Qualtrics (Survey system), OpenAir, FinancialForce (Professional Services), and Gainsight (commissions). They will analyze data sources, merging policies, and provide insights on how these elements relate to various business functions like Finance, Sales, and Marketing. The role will evolve from foundational knowledge to an authoritative understanding, driving data quality and governance across the organization.

2. Solutions Architecture :

The Architect will design and propose comprehensive, end-to-end solutions for data and analytics initiatives. This includes conducting high level impact assessments, and architecting scalable data pipelines, logical data models, BI implementations, and advanced analytical solutions. They will engage with stakeholders as part of the requirements gathering phases, advocate for innovative solutions, and present architectural proposals that demonstrate business value. As they progress, they will set standards for architectural practices and influence the strategic direction of data initiatives.

3. Cloud Knowledge :

The Architect will have strong proficiency in both Azure and GCP, with an emphasis on designing optimized cloud solutions. They will collaborate with Platform and DevOps teams to implement and enhance cloud services, ensuring alignment with organizational goals. Over time, they will act as strategic advisors for cloud initiatives, promoting best practices and mentoring teams on cloud-native architectures.

4. Data Engineering :

The Architect will bring solid expertise in data engineering principles, designing and implementing data pipelines that support high-volume data processing. They will lead efforts to optimize engineering processes, ensuring data quality and governance. As they advance, they will become recognized experts, influencing the strategic direction of data engineering practices and mentoring teams in modern frameworks. The architects will also have an integral knowledge of how the existing master pipelines are configured and an operational understanding of the capabilities of the existing frameworks and architecture.

5. Business Intelligence :

The Architect will be proficient in Power BI and responsible for designing enterprise-level BI solutions that integrate multiple data sources. They will recommend data solutions that optimize performance, collaborate with business units to align reporting strategies, and drive data-driven decision-making. As they grow, they will set the strategic vision for Self Service BI across the organization, fostering a culture of innovation and excellence in data storytelling.
Addition - Best practices, standards etc. that work best with the tool selected

6. Data Architecture & Modeling :

The Architect will design and validate complex data models that support analytics and reporting, ensuring best practices in data architecture are followed. They will lead the development of data modeling standards and collaborate with governance teams to ensure data security and compliance. Over time, they will establish the organizations data architecture strategy, influencing governance frameworks and emerging trends.
GCP Modeling

7. Machine Learning :

The Architect will design data solutions that effectively support the machine learning lifecycle and collaborate with data scientists to ensure data readiness. They will advocate for data-driven approaches to problem-solving, identifying opportunities for ML integration. As they progress, they will define the strategic direction for ML initiatives, serving as thought leaders and mentors in best practices.

8. Legacy Knowledge :

The Architect will navigate legacy systems, such as IBM Cognos, Informatica Cloud & Power Center, and Oracle/SQL data warehouses, to retrieve necessary information for key data initiatives. They will document critical processes within these systems and communicate their relevance to current initiatives. Over time, they will become immensely familiar with legacy systems, guiding their integration into modern solutions and mentoring others in best practices.

9. Training and Mentoring

The Architect will be instrumental in fostering a culture of learning and development within the organization.

Key responsibilities include :

- Stakeholder Training : Conduct sessions to facilitate change management and ensure effective adoption of new data solutions, enhancing user confidence and data literacy.

- Solution Reviews : Guide stakeholders through new solutions, highlighting functionalities and benefits to promote effective usage.

- Knowledge Sharing : Share advanced concepts in data architecture and analytics through workshops and documentation, encouraging continuous learning.

- Mentorship : Mentor junior team members and peers, providing guidance on best practices and fostering professional growth.

- Cross-Functional Collaboration : Collaborate with other data and analytics functions to identify training needs and develop tailored programs that address skill gaps.