Presales Data Architect - AWS

Requirements

• Provide technical pre-sales and post-sales support for analytics and data science engagements to prospective and existing customers. 
• Lead, define, and implement end-to-end modern data platforms in support of analytics and AI use cases. 
• Participate in customer-facing meetings to determine business and technical requirements that will be used in developing solutions. 
• Collaborate with CDOs, Enterprise Architects, Data Architects, Data Engineers, Data Scientists and provide technical product expertiseand prioritize use-cases for customers.  
• Define and capture customer success criteria to design, build, and manage end-to-end Proof-of-Concepts for our customers. 
• Document customer requirements, create statement of work for the services engagement and facilitate a clean hand-off to the post-salesprofessional services team. 
• Work alongside Account Executives to drive the deal strategy, helping address any knowledge gaps and build trust with the prospect through their journey towards becoming a customer. 
• Consistently improve current processes, making presentations, demos, and business case presentations more repeatable, scalable, and compelling. 

Technical Requirements

• Experience in delivering end-to-end analytics and data science solutions from idea conception through planning, requirements, design, development, testing, production and deployment/business process integration 
• 10+ years of data engineering and data science experience leading implementations of large-scale lakehouses and AI systems on AWS.  
• Prior experience in Glue, Sagemaker and Redshift is mandatory. Previous experience using Snowflake, Databricks, DBT and Airflow will be a plus.  
• Prior experience with lakehouse technologies like Hudi and Delta Lake and related infrastructure services, such as storage, firewall, security, key vault, etc., is required. 
• Prior experience with ML tools such as TensorFlow/Keras, PyTorch Lightning, HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray is required.  
• Prior experience in DataOps principles like CI/CD, pipeline and data observability, lineage, data catalog, and MLOps required.  
• Strong programming/scripting experience using SQL, Python, and Spark. 
• Experience with Agile development methods in data-oriented projects.