Snowflake - Data Engineer

Letitbex AI; Telangana; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Letitbex AI is seeking a Snowflake - Data Engineer with 5+ years of data engineering experience to design and optimize data pipelines for enterprise analytics. You will work on Snowflake architecture, performance tuning, and data products to deliver scalable AI-enabled insights.

This role emphasizes strong SQL, data modeling, data quality frameworks, and collaboration with AI/agentic technologies. Candidates should have hands-on Snowflake development and experience with large datasets,

Qualifications

• 5+ years of data engineering experience.
• 3+ years of hands-on Snowflake development experience.
• Experience supporting enterprise analytics, AI, or data product initiatives.

Skills

Snowflake development

SQL expert

Data modelling

Data quality

Job description

Letitbex AI is a fast-growing AI-driven technology company focused on building intelligent, scalable, and enterprise-grade solutions. We work at the intersection of AI, data engineering, cloud, and business transformation, helping organizations unlock real value from artificial intelligence.

Position: Snowflake - Data Engineer

Experience: 5+ Years

Notice Period: Can be considered up 15 Days

Required Qualifications

Experience

• 5+ years of data engineering experience.
• 3+ years of hands-on Snowflake development experience.
• Experience supporting enterprise analytics, AI, or data product initiatives.

Technical Skills

• Snowflake: Strong experience with Snowflake architecture, dynamic tables, materialized views, streams and tasks, secure views, schema design, query optimization, performance tuning, and warehouse optimization.
• SQL: Expert-level skills including complex joins, window functions, common table expressions (CTEs), analytical functions, query profiling, data transformations, and performance tuning. Comfortable working with datasets exceeding hundreds of millions of records.
• Data Modelling: Experience with dimensional modelling, semantic layers, data products, curated business views, KPI standardization, and metadata management.
• Data Quality: Hands-on experience implementing data validation frameworks, automated monitoring, data reconciliation, data observability, and root cause analysis.

AI & Agentic Technologies (Preferred)

Experience in one or more of the following:

• Retrieval systems and semantic search
• Large Language Models (LLMs) and prompt engineering

Preferred Experience

• Experience working with large-scale enterprise data platforms and diverse source systems.
• Experience supporting AI-powered analytical applications.
• Familiarity with process improvement or operational excellence methodologies (e.g., Lean, Six Sigma).