Principal Data Platform Architect (GCP)

Wipro

England

Hybrid

GBP 120,000 - 180,000

Full time

48 hours ago

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Job summary

Wipro is seeking a Principal Consultant - Data Engineering & Architecture to lead enterprise-scale cloud data platform design and delivery. You will shape data architectures on Google Cloud Platform, drive data product initiatives and mentor delivery teams across multi-disciplinary programs.

Join a global Data, Analytics & AI practice focused on scalable ETL/ELT frameworks, MDM, governance and performance. This role combines hands-on coding with strategic consulting, requiring strong stakeholder

Qualifications

Expert-level experience with Google Cloud Platform (GCP) or equivalent cloud data engineering platforms.
Advanced hands-on expertise in Python.
Proficient in SQL and dbt.
Strong experience designing and implementing modern ETL/ELT architectures.
Deep understanding of data modelling methodologies and best practices.
Proven experience building and deploying enterprise-scale data products from inception through production.
Experience implementing testing, validation, monitoring and data quality frameworks.
Strong understanding of DevOps, CI/CD and automation within data engineering environments.
Extensive experience designing enterprise data architectures and data platforms.
Expertise in Master Data Management (MDM) strategy, tooling and implementation.
Strong understanding of data governance, lineage, metadata management and integration patterns.
Experience evaluating and selecting enterprise data technologies and platforms.

Responsibilities

Lead the architecture, design and implementation of enterprise-scale cloud data platforms.
Design and develop robust, scalable ETL/ELT frameworks and data pipelines.
Build modern analytics and data product solutions that support reporting, AI, machine learning and operational use cases.
Deliver high-quality data engineering solutions leveraging Python, SQL, dbt and cloud-native services.
Drive the adoption of engineering best practices, standards and reusable frameworks across client programmes.
Ensure solutions are designed for scalability, performance, maintainability and operational excellence.
Define target-state enterprise data architectures aligned to business and technology strategies.
Lead data modelling activities including conceptual, logical and physical models.
Design integrated data ecosystems supporting analytics, operational reporting and AI-driven products.
Provide leadership in Master Data Management (MDM), enterprise data governance and metadata management initiatives.
Support technology evaluation, vendor selection and platform roadmap development.
Identify opportunities to utilise AI-assisted engineering capabilities to improve delivery quality, speed and productivity.
Support the development of data foundations required for AI and machine learning initiatives.
Partner with Data Science and AI teams to deliver production-ready data products.
Lead multidisciplinary delivery teams comprising engineers, architects, analysts and product specialists.
Provide technical governance and architectural oversight across programmes.
Mentor and coach engineering teams, fostering technical excellence and continuous learning.
Engage directly with senior client stakeholders to shape solutions, manage delivery risks and drive successful business outcomes.
Support solution development, estimation, proposals and client presentations.
Establish testing, validation and quality assurance frameworks for data products and pipelines.
Implement CI/CD, DevOps and DataOps practices across delivery teams.
Drive production readiness reviews, deployment planning and go-live activities.
Ensure compliance with security, governance, privacy and operational standards.