EY - GDS Consulting - AI And DATA - GCP - Manager

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The opportunity   We are seeking an experienced GCP Data Architect to design and implement scalable cloud-native data platforms, data lakes, and enterprise data warehouse solutions on Google Cloud Platform (GCP). The candidate will be responsible for defining/evaluating architecture standards, designing data integration frameworks, guiding engineering teams, and delivering business-focused analytics solutions .   Your key responsibilities

Design and implement enterprise-scale Data Lake and Data Warehouse solutions on GCP Well-versed with ETL process- SCD handling, incremental and historic loads, Failover processing, recovery and reprocessing of data pipelines, Data quality framework and controls  Define end-to-end data architecture (Lakehouse, event-driven) including ingestion, transformation, governance, security, and consumption layers  Develop cloud-native data integration solutions using Google Cloud services Architect data pipelines for multiple source systems such as fund administrations, SQL Server, APIs, and external platforms Design and develop pub/sub ingestion streams Implement data profiling, data quality, encryption, and compliance controls using GCP-native services. Establish orchestration frameworks and workflow automation strategies using Cloud Composer and Airflow  Lead solution design reviews and provide technical guidance to development teams  Collaborate with business stakeholders to translate business requirements into scalable data solutions.  Present architecture solutions to internal leadership and client stakeholder

Design & implement data mart (foundational and consumer marts)   Other Responsibilities

Implement design level technical best practices Interface and communicate with the client team and onshore coordinators Completion of assigned tasks on time and regular status reporting to the lead Agree on level of documentation with clients and track to sign of them. Work with client on design approvals. Help client select tools and technologies necessary for the scope of the project. Define and develop client specific best practices around data management within a cloud environment Recommend design alternatives for data ingestion, processing and provisioning layers Design and develop data ingestion programs to process large data sets in Batch mode using Spark, or similar technologies

Required Skills (Mandatory)

Strong understanding & familiarity with all GCP ecosystem components Strong understanding of underlying GCP Architectural concepts and distributed computing paradigms Hands-on programming experience in Apache Spark using Python/Scala and Spark Streaming Hands on experience with major big data components in GCP like GCP Data Proc, Big Query, Google Pub Sub, Google Data Flow Experience in designing and implementing data marts (foundational and consumer marts) Hands-on experience on SQL and Datawarehouse Experience working with NoSQL in at least one of the data stores like GCP Firestore, GCP Datastore, GCP Big Table or MonogBD ATLAS Knowledge of Spark and Kafka integration with multiple Spark jobs to consume messages from multiple Kafka partitions Solid understanding of ETL methodologies in a multi-tiered stack Familiarity with financial data products and domains- preferably asset wealth management data products (public/private markets) Experience in converting business problems/challenges to technical solutions considering security, performance, scalability etc. Experience in Enterprise grade solution implementations. Experience in performance bench