PwC
Digital and Cyber - Data and Cloud - Data and AI - Senior Manager
- Permanent
- Riyadh, Saudi Arabia
- Experience 10 - 15 yrs
- Urgent
Job expiry date: 29/11/2025
Job overview
Date posted
15/10/2025
Location
Riyadh, Saudi Arabia
Salary
SAR 30,000 - 40,000 per month
Compensation
Comprehensive package + relocation
Experience
10 - 15 yrs
Seniority
Senior Manager
Qualification
Bachelors degree
Expiration date
29/11/2025
Job description
PwC Middle East seeks a Senior Manager within Digital and Cyber - Data and Cloud - Data and AI to lead multi-engagement delivery from strategy to execution, aligning client data strategies to business strategy and migrating organizations to modern cloud data environments. The role requires deep understanding and experience with modern cloud data architectures and engineering on AWS, Microsoft Azure, and Google Cloud Platform, and hands-on leadership across data modeling techniques (file-based, normalized, denormalized, star schemas, schema on read, Vault data model, graphs) for mixed workloads (OLTP, OLAP, streaming). Responsibilities include architecting native cloud data implementation patterns spanning data ingestion & integration (ingress and egress), data storage (raw & cleansed), data preparation & processing, master & reference data management, data virtualization & semantic layer, and data consumption & visualization; implementing cloud data solutions considering business applications, cost optimization, strategic needs and future growth to become data-driven; applying leading practices for high availability, scalable, process- and storage-intensive architectures for data integration/migration, analytics and insights, AI and ML requirements; and producing high-quality documentation for cloud data architecture. The Senior Manager will oversee implementation using platform-native and ecosystem tools such as AWS Glue, Azure Data Factory, Event Hub, Databricks, Redshift, Azure Synapse, BigQuery, Snowflake, and Infrastructure as Code (CloudFormation, Terraform), with working knowledge of CI/CD, cloud DevOps, containers, and programming (Python/PySpark/JavaScript). The role also covers enterprise data concepts (Master Data Management, Enterprise Data Warehouse), SQL and visualization (Tableau/Power BI), and leading data architecture teams to create cloud data migration/integration/warehouse plans, roadmaps, success metrics, and assessments of enterprise on-prem and cloud data systems while navigating global teams and engagements, advising stakeholders, and upholding PwC’s code of ethics and business conduct.
Required skills
Key responsibilities
- Lead multiple client engagements to design, architect, and implement modern cloud data solutions on AWS, Azure, and GCP using data modeling techniques (normalized, denormalized, star schemas, schema on read, Data Vault, graphs) for OLTP, OLAP, and streaming workloads.
- Architect native cloud data implementation patterns covering data ingestion and integration (ingress/egress), storage layers (raw and cleansed), data preparation and processing, master and reference data management, data virtualization and semantic layers, and data consumption and visualization.
- Implement cloud data platforms and solutions leveraging AWS Glue, Azure Data Factory, Event Hub, Databricks, Redshift, Azure Synapse, BigQuery, Snowflake, and Infrastructure as Code (CloudFormation, Terraform) aligned to business applications, cost optimization, and growth goals.
- Apply leading practices to deliver high-availability, scalable, process- and storage-intensive architectures that support data integration/migration, analytics and insights, and AI/ML requirements, and ensure high-quality cloud data architecture documentation.
- Define cloud data roadmaps, migration and integration plans, success metrics, and assessments of enterprise data systems (on-prem and on-cloud) while navigating global teams and engagements and building trust with stakeholders through open, honest conversations.
- Advise stakeholders on technical issues, establish root causes rather than symptoms, and move between big-picture thinking and relevant detail to develop specialized expertise in one or more areas of Data & AI.
- Lead adoption of enterprise data concepts, including Master Data Management and Enterprise Data Warehouse, and oversee SQL-based reporting and visualization (Tableau/Power BI) and programming (Python/PySpark/JavaScript) as needed.
- Promote and review CI/CD and cloud DevOps practices and related tooling to industrialize data engineering and analytics delivery, including familiarity with containers and platform services.
- Uphold PwC Professional expectations: invite diverse voices, initiate coaching conversations, uphold ethics and business conduct, and align delivery with market priorities and firm strategy.
Experience & skills
- Hold a Bachelor Degree (minimum); bring a minimum of 10 years of experience with demonstrable delivery in Data & AI, data architecture, and cloud data engineering.
- Demonstrate understanding and hands-on experience with modern cloud data architectures on one or more providers (AWS, Azure, GCP), including platform selection, definition of data needs, and migration to cloud data environments.
- Show proven leadership designing and implementing native cloud data solutions across ingestion/integration, storage, preparation/processing, MDM/reference data, data virtualization/semantic layer, and consumption/visualization.
- Exhibit experience designing data models (file-based, normalized, denormalized, star schemas, schema on read, Data Vault, graphs) across mixed workloads (OLTP, OLAP, streaming).
- Implement solutions using tools such as AWS Glue, Azure Data Factory, Event Hub, Databricks, Redshift, Azure Synapse, BigQuery, Snowflake, and Infrastructure as Code (CloudFormation, Terraform).
- Apply leading practices for high-availability and scalable architectures supporting integration/migration, analytics and insights, AI and ML, and produce high-quality architecture documentation.
- Demonstrate familiarity with CI/CD, cloud DevOps, containers, and programming (Python/PySpark/JavaScript), with strong SQL and visualization experience (Tableau/Power BI).
- Possess knowledge of enterprise data concepts including Master Data Management and Enterprise Data Warehouse, and experience with MDM standards.
- Preferably hold certifications in AWS/Azure/GCP data engineering and have a track record leading data architecture teams to create cloud data migration/integration/warehouse plans, roadmaps, success metrics, and enterprise assessments.
