AI & Data Engineer: Snowflake Platform Architect

IBM; Columbia (SC); On-site; USD 120,000 - 160,000; Full time

Job summary

IBM Consulting in the United States seeks a Consultant, AI and Data Engineer to build Snowflake Data Cloud foundations and AI solutions for enterprise clients. You will work on data ingestion, modeling, governance, and deployment across AI use cases and traditional ML.

Collaboration with solution architects, data scientists, and analysts is essential to deliver production-grade pipelines in a fast-paced, client-facing environment.

Qualifications

• Spanning data engineering (data management, database development, ETL / ELT, data warehousing) and applied AI or machine learning; consulting or professional services experience is highly desirable.
• Strong SQL and Python; experience with dbt, Spark, or Snowpark for transformation.
• Experience building ETL / ELT ingestion pipelines and developing data warehouses on a cloud data platform (Snowflake preferred; Redshift, BigQuery, Databricks also relevant).
• Hands-on experience building LLM-based applications: prompt engineering, retrieval-augmented generation, vector stores and embeddings, and orchestration frameworks (e.g. LangChain, LlamaIndex).
• Working knowledge of ML fundamentals and the tradeoffs between LLM, classic ML, and rules-based approaches.
• Proficiency with cloud platform services for data and AI workloads (AWS, Azure, or GCP).
• Experience with software engineering practices: Git-based version control, automated testing, CI/CD, and code review.

Responsibilities

• Data Pipeline Development: Design, build, and operate ETL / ELT ingestion pipelines and data warehouse / lakehouse models on Snowflake, including structured and unstructured sources feeding downstream analytics and AI use cases.
• AI Solution Development: Build, evaluate, and deploy LLM-based applications (RAG, agents, document intelligence, conversational interfaces) and classical ML models.
• AI-Ready Data Engineering: Prepare, chunk, embed, and govern data for AI consumption, including vector search, feature pipelines, and semantic layers.
• Snowflake AI Platform: Implement solutions using Snowflake Cortex (LLM functions, Cortex Search, Cortex Analyst, Cortex Agents), Snowpark, and related services.
• Evaluation and Reliability: Define evaluation datasets and metrics for AI outputs, implement testing, observability, and guardrails.
• Implementation and Deployment: Deploy solutions to cloud environments (AWS, Azure, GCP, Snowflake) with CI/CD, version control, and infrastructure-as-code practices.
• Client Engagement: Understand client requirements, present technical options and trade-offs, and work with client teams to integrate data and AI solutions into their business processes.
• Governance and Security: Apply data governance, privacy, and responsible AI practices, including PII handling, role-based access, and auditability.
• Documentation and Knowledge Transfer: Produce clear documentation for pipelines, models, prompts, and architectures to enable client handoff and internal reuse.
• Continuous Learning: Track developments in the Snowflake and AI ecosystems and bring practical recommendations to engagements and to the practice.

Skills

SQL

Python

Data pipeline design

ETL/ELT

AI concepts

Cross-functional collaboration

Problem solving

Education

Master's Degree

Tools

Snowflake

Snowpark

Snowflake Cortex

LangChain

LlamaIndex

dbt

Git

CI/CD

Job description

IBM Consulting in the United States seeks a Consultant, AI and Data Engineer to build Snowflake Data Cloud foundations and AI solutions for enterprise clients. You will work on data ingestion, modeling, governance, and deployment across AI use cases and traditional ML.

Collaboration with solution architects, data scientists, and analysts is essential to deliver production-grade pipelines in a fast-paced, client-facing environment.