The role holder is responsible for developing and maintaining the overall digital data architecture and roadmap, while providing technical leadership and advisory support across the organization. The position focuses on evaluating current data architectures, identifying gaps, defining the target state, and developing the transition roadmap. The role holder is also responsible for establishing data architecture principles and ensuring all activities comply with the organization’s policies and procedures.

KEY RESPONSIBILITIESKey ResponsibilitiesCore Responsibilities

- Define and govern the enterprise frameworks, standards, pipeline architectures, and processes that manage data flows between OLTP systems and the Lakehouse, ensuring accuracy, consistency, and alignment with enterprise data principles.
- Define and govern the standards, processes, and best practices for establishing the Data Fabric architecture including the enterprise metadata catalog and the unified data access layer to ensure an integrated, discoverable, GenAI-enabled, and consistent enterprise data ecosystem.
- Develop optimization-focused solution architectures and provide domain-specific high-level architectural guidance to address data inconsistencies and integrity issues, improving data quality, optimizing storage, and reducing overall costs.
- Authorized to review, endorse, and co-sign architecture blueprints for all systems and solutions within the data platform to ensure full alignment with the enterprise Data Architecture.
- Ensure to update the Architecture repository with relevant architecture’s artifacts/deliverables, and architectural roadmap.
- Define and maintain the architecture principles, frameworks, guidelines, and roadmap for Technology Architecture Governance, ensuring alignment with the relevant group-level Architecture Governance &
- Enablement function, and providing oversight across stc group subsidiaries.
- Manage end to end architectural engagements such as blueprinting and assessments in line with the defined architecture development processes, and identify gaps between the As-Is and To-Be data architectures to define the required transition architecture and roadmap.
- Evaluate and assess the as-is architecture and conduct the assessment to define the to-be architecture for specific technology and business domains.




- Ensure to support Technology Excellence &
- Control to translate architecture roadmap into materialized demands and executable projects/programs as needed.
- Evaluate and review technical & architecture proposals such as RFIs &
- RFP and provide the needed feedback and insights.
- Develop, maintain, and govern the principles, guidelines, policies, and reference architectures for functional and line-of-business domains, supported by continuous trend analysis and market research to ensure the adoption of the most relevant and effective architectural models and patterns.
- Identify and conduct technology efficiency and optimization studies, and translate their findings into roadmap items with clear, measurable qualitative and quantitative outcomes.
- Support architecture-related change management reviews, including ARB decisions, RFP reviews, and architecturally significant change requests.
- Enhance and provide architectural insight into demand management reviews for TU initiatives and new business capabilities, ensuring alignment with enterprise architectural direction.
- Define the architectural standards and enablement frameworks for AI and ML workloads, including model lifecycle governance, data readiness, feature engineering pipelines, and integration with the enterprise data fabric to ensure scalable, secure, and compliant AI adoption across the organization.
- Define and govern the data readiness and integration requirements for GenAI initiatives, ensuring that enterprise systems, data sources, and the lakehouse platform provide the structured, unstructured, and real-time data needed to enable scalable, accurate, and trustworthy GenAI capabilities.

MINIMUM QUALIFICATIONS, EXPERIENCE, SKILLS &

- COMPETENCIESQualifications





- Master’s degree in Telecommunications Science and Technology / Telecommunications systems / Electronics and Electrical Communications or related Engineering discipline or Science or Business Administration (specializing in Systems) Preferred.
- Bachelor’s degree in Telecommunications Science and technology / Computer Science or a related Data Engineering Discipline or Science.

Professional Certifications Preferred

- Preferred certifications in Enterprise Architecture such as TOGAF, Zachman, or equivalent.

Years of Experience A minimum of 12 years of relevant experience in the data domain, including at least 5 years in a similar data enterprise architecture role.

Nature of Experience

- Prior experience in managing large scale Technology/data/AI Architecture Transformation and Implementation programs.
- Preferred prior experience in leading large scale technology organizations (Data or IT).
- Exposure to emerging trends and technologies in previous roles.

Job Specific Knowledge and Skills
- Strong leadership skills with the ability to influence C-level executives.
- Strong knowledge of the telecom industry, technology innovation, and the vendor/platform landscape.
- Deep expertise in data management, Data Lake, Lakehouse, and EDW ecosystems.
- Strong change management capabilities.
- Strong decision-making and problem-solving skills.
- Strong knowledge of enterprise technologies and integration patterns.
- Strong understanding of digital architecture concepts, frameworks, and principles.
- Strong knowledge of Data Fabric, metadata management, and unified data access layers.
- Strong understanding of AI/ML and GenAI data readiness requirements.
- Experience with cloud-native data platforms and modern data architectures.
- Strong knowledge of key data platform technologies such as Teradata, Databricks, Hadoop-based platforms, and contemporary Lakehouse architectures.

Business Language Skills
- English Language proficiency level is fluent.

Skills: data quality & data governance,ai/ml data architecture & readiness,cloud-native data platforms,data fabric / metadata management,enterprise data architecture,unified data access layer,genai data readiness & integration,enterprise architecture governance,data integration & enterprise integration patterns,data lake / edw,oltp to lakehouse architecture,data lakehouse / data platform architecture,architecture roadmap & transformation,data engineering & data pipelines,databricks / teradata / hadoop

📌 Senior Digital Data Architect (Hyderabad)
🏢 Aarushi Infotech
📍 Hyderabad