Data Engineer

Data Engineer

Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.

**skills : Snowflake Data Warehouse Data Engineering, Data Building Tool, Gen AI, Fivetran

Minimum 8 year(s) of experience is required with Snowflake+GenAI

Job Description - Snowflake Architect

Role Description : Lead design and implementation of scalable, secure, and high-performance Snowflake architectures across multiple projects and teams. Contributes to CoE initiatives by creating guidelines, frameworks, and reference architectures to ensure consistency and scalability across projects.

**skills : Snowflake Data Warehouse with GenAI

Snowflake Experience: Minimum 3 years

Certifications: SnowPro Core Certified(must)

Summary:

As a Snowflake Architect, you will design and implement scalable, secure, and high-performance Snowflake architectures across multiple projects and teams. Your typical day will involve collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models, while also engaging in discussions to refine and enhance the overall data architecture. You will be involved in various stages of the data platform lifecycle, ensuring that all components work harmoniously to support the organization's data needs and objectives. From CoE perspective, you will collaborate closely on presales, support delivery teams, and lead the design and execution of POVs and POCs including GenAI features.

Roles & Responsibilities:

- Lead Snowflake solutions across data ingestion, storage, transformation, and access.

- Lead capability growth initiatives by mentoring team members, driving POCs, and contributing to knowledge repositories.

- Provide pre-sales support, including proposal creation, estimations, solutioning, and client presentations.

- Define data modeling standards, physical schema designs, and best practices for structured and semi-structured data.

- Familiar with Snowflake s advanced features, including Snowpark, Iceberg tables, dynamic tables, snowpipe streaming, SPCS, authentication & authorization methods, alerts, performance tuning, row level security, masking, tagging, etc.

- Stay abreast of evolving Snowflake and GenAI capabilities recommend and pilot new tools and frameworks.

- Collaborate with AI/ML teams to enable GenAI use cases leveraging Snowflake s native capabilities (e.g., Cortex-AI, Streamlit apps, LLM models, Agentic-AI framework).

-- Understanding of LLM functions, Cortex Analyst(text to SQL), Streamlit app(for bots), Document-AI, Cortex Search should be there.

-- Have implementation experience on Gen-AI features within Snowflake that can be of creating POCs/POVs, MVPs, etc.

Professional & Technical Skills:

- Proficiency in Snowflake Data Warehouse, SnowPro Core Certification

- Experience or Knowledge of building or integrating Generative AI applications and experience with Snowflake Cortex.

- Strong communication skills.