Data Lead – Snowflake

We are looking for a skilled Data Engineer with extensive experience in Snowflake and a strong background in developing AI-powered data solutions using Snowflake Cortex. The successful candidate will be responsible for designing scalable data pipelines, optimizing data models, and integrating advanced AI capabilities such as large language models (LLMs), retrieval-augmented generation (RAG), and AI-driven analytics within the Snowflake environment. This role requires a hands-on approach to building efficient, secure, and cost-effective data architectures that support both analytics and AI workloads.

Key Responsibilities

Design, develop, and optimize scalable ETL/ELT data pipelines leveraging SQL, Python, Snowpark, Snowpipe, Streams, Tasks, and Dynamic Tables. Build and maintain robust data models, including dimensional and medallion architectures, to facilitate analytics and AI applications. Develop AI-powered solutions using Snowflake Cortex features such as LLM functions, Cortex Search for RAG, and Cortex Analyst for natural language-to-SQL translation.

Process both structured and unstructured data, including PDFs and images, to enable comprehensive analytics and AI insights. Create interactive data applications and AI-driven interfaces using Streamlit within the Snowflake platform. Continuously optimize query performance, warehouse utilization, and processing costs while monitoring AI token usage to ensure efficiency.

Implement role-based access control (RBAC), data masking, security policies, and enforce data governance best practices to maintain data integrity and compliance. Establish and maintain CI/CD pipelines and version control workflows using Git alongside infrastructure-as-code tools such as dbt and Terraform. Ensure data quality through rigorous checks, pipeline monitoring, and orchestration to guarantee data accuracy, reliability, and availability.

Collaborate closely with cross-functional teams to translate complex business requirements into scalable data and AI solutions. Provide mentorship to junior engineers and contribute actively to engineering best practices, including code reviews and comprehensive technical documentation.

Required Qualifications

A minimum of 6 years of experience in data engineering, with at least 3 years dedicated to hands-on work with Snowflake. Advanced proficiency in SQL and Python for data transformation, pipeline development, and performance tuning. Strong practical experience with Snowflake components including Snowpark, Snowpipe, Streams, Tasks, and Dynamic Tables.

Demonstrated expertise in Snowflake Cortex capabilities, such as LLM functions, Cortex Search, and Cortex Analyst. Solid understanding of large language models, embeddings, vector search, and retrieval-augmented generation (RAG) techniques. Proven experience in data modeling, ETL/ELT development, and workflow orchestration using Airflow or similar tools.

Familiarity with at least one major cloud platform—AWS, Microsoft Azure, or Google Cloud Platform (GCP). Experience with Git, CI/CD methodologies, and automated deployment pipelines. Comprehensive knowledge of data security principles, access management, governance frameworks, and data quality assurance.

Strong analytical thinking, problem-solving abilities, and excellent communication and collaboration skills to work effectively across teams.

Preferred Qualifications and Benefits

While not explicitly stated, candidates with additional experience in developing AI-powered interactive applications using Streamlit and those familiar with infrastructure-as-code tools like Terraform and dbt will have an advantage. The role offers the opportunity to work at the forefront of AI and data engineering within a cutting-edge Snowflake environment, contributing to innovative solutions that drive business value.

This position is ideal for professionals seeking to deepen their expertise in AI-integrated data engineering and to play a pivotal role in shaping scalable, secure, and intelligent data ecosystems.