Job Summary : As a GCP Data Engineer, you will lead technology innovation for our clients through robust delivery of world-class solutions. This includes integrating native GCP services and third-party technologies to architect scalable data warehouses, data lakes, and analytics platforms. You will be responsible for architecting transformation and modernization of enterprise data solutions on GCP integrating native GCP services and 3rd party data technologies. You’ll work with implementation teams, managing everything from data ingestion to visualization in complex client environments. We are looking for candidates who have a broad set of technology skills across these areas and who can demonstrate an ability to design right solutions with appropriate combination of GCP and 3rd party technologies for deploying on GCP cloud. Key Responsibilities : Lead a team in designing, developing, and deploying high-performance data analytics solutions. Provide technical expertise from concept to operations, ensuring the successful deployment of large-scale data solutions. Build secure and reliable data-centric services in GCP. Implement end-to-end data analytics for complex environments, including data ingestion, transformation, and visualization. Provide thought leadership on Big Data and analytic strategies for clients. Support data migration and transformation projects, leveraging Google AutoML to enhance pipeline intelligence. Required Experience: Data Platform Architecture: 3+ years of experience with GCP data engineering, ingestion, and curation. Data Modeling & Optimization: 3+ years of experience designing data models on GCP using BigQuery and BigTable. Vertex AI: 1+ years of experience building and managing machine learning models. MLOps for GenAI: 1+ years of implementing MLOps for GenAI model deployment. Qualifications : Extensive experience in large-scale architecture, solution design, and operationalization of data warehouses, data lakes, and analytics platforms on GCP is essential. Strong knowledge of GCP services, with at least 5 years in cloud platforms and 2+ years of deep experience in GCP data services (e.g., Spark, DataProc, Dataflow, BigQuery, Pub/Sub). 3+ years of experience re-architecting data warehouses on GCP, designing and building production data pipelines using Java and Python. Hands-on experience with GCP data lakes and ingestion solutions. Experience with metadata management, Hadoop/NoSQL, performance engineering, and self-service data preparation tools like Trifacta or Paxata. Bachelor's degree or equivalent work experience. Google Certified Professional Data Engineer certification or Google Professional Machine Learning Engineer certification required. #J-18808-Ljbffr The Data Sherpas
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