Description

You will design and implement scalable data architectures across multi-cloud environments, ensuring performance, reliability, and alignment with business goals.

This role is on-site.

Responsibilities

• Architect and optimize data solutions using Snowflake, Databricks, and cloud platforms (AWS, Azure, GCP).
• Design Data Warehousing, Data Lakes, and Lakehouse architectures to support complex analytics.
• Develop and deploy AI/GenAI solutions, including LLM integrations, RAG architectures, and agentic workflows.
• Optimize SQL performance, indexing, partitioning, and compute-warehouse scaling for large-scale datasets.
• Manage stakeholder expectations and provide technical guidance in presales and delivery contexts.

Required Skills

• 12+ years total IT experience, with 4+ years as a hands-on Data or Enterprise Architect.
• Hands-on architectural experience across AWS, Microsoft Azure, and Google Cloud Platform (GCP).
• Deep expertise in Snowflake and Databricks for modern data stack implementation.
• Master-level SQL proficiency, including complex query optimization and performance tuning.
• Strong coding skills in Python and PySpark for data engineering and AI workflows.
• Practical experience with Large Language Models (LLMs), Generative AI, and prompt engineering.
• Bachelor's degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Experience building quick AI POCs and integrating cloud AI services.
• Proven track record in consulting, stakeholder management, and presales environments.

Key Skills

Education

Bachelor's degree