Data Presales Consultant
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Job Location:
Atlanta, GA - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
Title : Data Presales Consultant
Location : Atlanta GA
Hire Mode: Contract
Location : Atlanta GA
Hire Mode: Contract
Job Description
Role Summary
We are looking for a Data Presales professional with strong Generative AI (GenAI) experience to support enterprise customers. This role involves pre-sales solutioning GenAI use-case design customer demos and proposal support across data platforms analytics and AI/ML solutions.
We are looking for a Data Presales professional with strong Generative AI (GenAI) experience to support enterprise customers. This role involves pre-sales solutioning GenAI use-case design customer demos and proposal support across data platforms analytics and AI/ML solutions.
Key Responsibilities
Partner with Sales and Account teams to understand customer business challenges and translate them into data analytics and GenAI solutions.
Design end-to-end data architectures including data ingestion processing analytics and AI/ML layers.
Define and demonstrate GenAI use cases such as:
o AI copilots and chatbots
o Document intelligence and summarization
o Predictive and prescriptive analytics
o Natural language query and insights
o Enterprise knowledge assistants using structured and unstructured data
Build and present POCs demos and technical presentations to business and technical stakeholders.
Support RFP/RFI responses solution proposals and technical documentation.
Collaborate with delivery product and engineering teams to ensure solution feasibility and scalability.
Stay current with advancements in GenAI LLMs and cloud AI services.
Design end-to-end data architectures including data ingestion processing analytics and AI/ML layers.
Define and demonstrate GenAI use cases such as:
o AI copilots and chatbots
o Document intelligence and summarization
o Predictive and prescriptive analytics
o Natural language query and insights
o Enterprise knowledge assistants using structured and unstructured data
Build and present POCs demos and technical presentations to business and technical stakeholders.
Support RFP/RFI responses solution proposals and technical documentation.
Collaborate with delivery product and engineering teams to ensure solution feasibility and scalability.
Stay current with advancements in GenAI LLMs and cloud AI services.
Required Skills & Experience
8 years of experience in Data Analytics AI/ML or related domains with exposure to presales or customer-facing roles.
Strong knowledge of data platforms and analytics ecosystems:
o Data lakes data warehouses ETL/ELT pipelines
o Snowflake Databricks BigQuery Redshift (any)
Proven hands-on experience with GenAI including:
o Large Language Models (LLMs)
o Prompt engineering and prompt optimization
o RAG (Retrieval-Augmented Generation) frameworks
o Vector databases (Pinecone FAISS Weaviate etc.)
Experience with cloud platforms: AWS Azure or GCP.
Proficiency in Python SQL and REST APIs.
Strong presentation communication and stakeholder management skills.
8 years of experience in Data Analytics AI/ML or related domains with exposure to presales or customer-facing roles.
Strong knowledge of data platforms and analytics ecosystems:
o Data lakes data warehouses ETL/ELT pipelines
o Snowflake Databricks BigQuery Redshift (any)
Proven hands-on experience with GenAI including:
o Large Language Models (LLMs)
o Prompt engineering and prompt optimization
o RAG (Retrieval-Augmented Generation) frameworks
o Vector databases (Pinecone FAISS Weaviate etc.)
Experience with cloud platforms: AWS Azure or GCP.
Proficiency in Python SQL and REST APIs.
Strong presentation communication and stakeholder management skills.
Nice to Have
Experience with enterprise or industrial data platforms.
Knowledge of MLOps model deployment governance and AI security.
Exposure to BI and visualization tools (Power BI Tableau Looker).
Cloud or AI-related certifications (AWS Azure GCP).
Experience working in large-scale enterprise environments.
Experience with enterprise or industrial data platforms.
Knowledge of MLOps model deployment governance and AI security.
Exposure to BI and visualization tools (Power BI Tableau Looker).
Cloud or AI-related certifications (AWS Azure GCP).
Experience working in large-scale enterprise environments.
Education
Bachelors or Masters degree in Computer Science Data Science Engineering or related field.
Bachelors or Masters degree in Computer Science Data Science Engineering or related field.
Key Skills
- Electro Mechanical
- Joomla
- Academics
- CMS
- Benefits
