As a Senior Data Engineer specializing in Snowflake and Generative AI, you will be at the forefront of building robust, scalable data architectures that power next-generation AI applications.

You will work closely with cross-functional product and data science teams to design end-to-end pipelines, ensuring that data is not only accessible but optimized for Large Language Model (LLM) integration. Your work will directly influence the efficiency of AI-driven business insights and the performance of complex data-intensive applications, making you a critical contributor to the organization's technical roadmap.

Key Responsibilities :

- Architect and maintain high-performance data warehouses using Snowflake to support complex analytical and AI-driven workloads.

- Design and implement efficient ELT pipelines using Data Build Tool (dbt) to ensure data quality, consistency, and lineage across the enterprise.

- Integrate Large Language Models (LLMs) into existing data ecosystems using Langchain and Langgraph to enable advanced natural language processing capabilities.

- Execute rigorous cost optimization strategies within the Snowflake environment to maximize performance while minimizing cloud infrastructure expenditure.

- Develop and enforce sophisticated data modeling standards to support scalable reporting and machine learning initiatives.

- Implement DevOps best practices for data engineering, including CI/CD automation and infrastructure-as-code, to streamline deployment cycles.

- Collaborate with stakeholders to translate business requirements into technical specifications, ensuring data solutions align with organizational goals.

Required Skillset :

- Demonstrated expertise in Snowflake SQL and advanced data warehousing techniques, with a proven ability to handle large-scale datasets.

- Proficiency in building and managing ELT workflows using Data Build Tool (dbt) and orchestrating complex data transformations.

- Hands-on experience in developing AI-enabled applications using Langchain and Langgraph frameworks to interface with Large Language Models.

- Strong analytical skills in data modeling, capable of designing schemas that support both traditional BI and modern AI/ML use cases.

- Ability to manage cloud infrastructure costs effectively, with a deep understanding of Snowflake's resource monitoring and optimization features.

- Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders and work effectively in a hybrid or on-site environment across Gurgaon, Bangalore, or Pune.

- A minimum of 6 to 11 years of professional experience in data engineering or a related technical field, with a track record of delivering production-grade data solutions.