GCP Data Architect

Responsibilities

• Responsible for defining enterprise level Data modernization & transformation solution on Google Cloud Platform and adoption strategy for customers
• Architecture and solution design of cloud data strategy and platform aligned with the business objectives
• Responsible for evaluating the google cloud native services and other technologies for our customer needs and recommending the best fit for them aligning to their future vision and strategy
• Work collaboratively with various teams across geographies and contribute to build, evangelize data architecture & AI/ML best practices, re-usable assets and solutions
• Based on Customer specific requirements and use cases, architect solutions and end to end ownership of iterating and ensuring the solutions are deployed and fit for purpose
• Design and streamline enterprise data architectures and pipelines and architect solutions which are intuitive, interoperable, extensible, scalable and are continuously learning and improving
• Expected to travel to assigned customers/engagements(average 50%)

Requirements

• 12+ years of experience working in Enterprise Data Warehouse technologies
• Minimum needed certifications: Google Cloud Certified Professional Cloud Architect/Google Cloud Certified Professional Data Engineer
• Preferred additional certifications: Google Cloud Professional ML Engineer, Other Cloud (AWS/Azure) Data & AI/ML related certifications
• Solid in-depth hands-on experience and understanding of data lakes and data warehouse architectures,
• designs, implementations and hybrid data architectures on Google cloud, other clouds and migration of on-prem to cloud
• Experience in handling structured and unstructured data from many sources and deep knowledge about batch and streaming data processing methods
• Solid understanding of data virtualization, data catalogues, metadata management, data ingestion, data visualization, data governance, security and data quality management frameworks, tools and evolving technology landscape
• Deep experience in implementing enterprise data lake or data house modernization programs
• Customer facing migration & modernization experience, including discovery, assessment, planning, design, implementation and Data& ML Ops
• Extensive hands on experience with SQL, Databricks, Unity Catalog, BigQuery, PySpark
• Experience with building software code in one or more languages such as Java, Python and SQL
• Deep understanding and working experience on advanced analytics, AI algorithms and Machine Learning techniques
• Work experience with geographically distributed teams and off-shore models
• Excellent verbal and written communication skills, facilitation and presentation skills
• Ability to interact professionally with a diverse group of stakeholders (senior executives, operations, customer service & partners)
• Enjoys working in an autonomous, dynamic, and challenging environment.
• Team player who enjoys fluidity, change, and flexible working arrangements
• Self-starter & a team player who enjoys fluidity, change, and flexible working arrangements, wants to get involved, make a difference, enjoys working in a dynamic, and fast paced environment

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