Data Engineer- Snowflake Cortex- SPCS

InfoCepts; India; On-site; INR 2,000,000 - 3,500,000; Full time

Job summary

InfoCepts is hiring a Data Engineer specialized in Snowflake Cortex and Cortex Agents to design scalable, secure data ecosystems. You will build semantic models, integrate RESTful APIs, and develop AI-powered analytics interfaces across Snowflake, Streamlit, and enterprise apps.

You will collaborate with architects, data engineers, and DevOps to enable analytics, AI, and BI use cases while ensuring RBAC compliance and data governance across platforms.

Qualifications

• 2+ years in data engineering or AI/ML analytics with Snowflake and Python.
• Experience with semantic modelling, logical tables, and verified queries in Snowflake.
• Exposure to Cortex Analyst, Cortex Search, and AI-driven analytics.

Responsibilities

• Design, develop, and optimise cloud-native data solutions on Snowflake Cortex.
• Lead migration and modernization of AI solutions into Snowflake AI Data Cloud.
• Develop AI-powered apps using Python, Streamlit, and APIs within Snowflake/React frontend.

Skills

Snowflake

Cortex Analyst

Semantic Modelling

Python

RESTful API

Streamlit

RBAC & Data Governance

LLMs & AI/ML

CI/CD

Docker

Kubernetes

Snowpark

Education

Bachelor’s or Master’s in CS/DS/IT

Tools

Snowflake Cortex

Snowflake Docs & Security

Python

Streamlit

AWS/Azure/GCP

Terraform

Docker

Job description

Position:

Data Engineer-Snowflake Cortex-SPCS

Purpose of the Position:

We are seeking a Snowflake Cortex, SPCS Data Engineer with expertise Cortex Agents, Semantic Modelling to support enterprise-scale data platform initiatives. The role involves designing, developing, and optimising cloud-native data solutions, while contributing to the migration and modernisation of data workloads in Snowflake. The individual will work closely with architects, data engineers, DevOps teams, and business stakeholders to build scalable, secure, and high-performing data ecosystems that support analytics, AI and business intelligence needs.

Type of Employment:

Full-time

Key Result Areas and Activities:

• Conversational Analytics Development: Build intelligent analytics interfaces using Snowflake Cortex Analyst.
• Semantic Modelling: Create and maintain semantic models in YAML to support accurate text-to-SQL translation.
• API Integration: Integrate RESTful APIs into chat interfaces and business tools like Slack, Teams, and custom apps.
• Data Governance & Security: Ensure compliance with Snowflake’s RBAC and privacy standards across all solutions.
• Performance Optimization: Continuously improve the accuracy and efficiency of AI-powered analytics workflows.
• Host Python application, ML model, Streamlit app, or API against Snowflake datawithin the Snowflake ecosystem providing better security, governance, and reduced data movement

Roles and Responsibilities

Essential Skills:

• Strong hands-on experience with Snowflake and working knowledge of Streamlit.
• Working Knowledge Cortex Analyst and AI/ML capabilities.
• Basic knowledge in Python for data engineering, automation, and API integration.
• Experience building interactive applications using Streamlit or similar frameworks.
• Deep understanding of semantic modeling, logical tables, and verified queries in Snowflake.
• Familiarity with LLMs, generative AI, and conversational interfaces.
• Knowledge of RESTful API design and integration.
• Experience with RBAC, data governance, and secure data handling practices.
• Data Engineering, ETL / ELT, Incremental data processing, Dimensional modelling, Stored Procedures.
• Snowflake, Advanced SQL, LLM Prompt Engineering, LLM Response Tuning
• Experience with Snowflake Cortex Analyst, Snowflake Semantic Views, Snowflake Cortex Search, Snowflake Cortex Agents, Semantic modelling, Natural-language-to-SQL solutions, RAG / semantic retrieval concepts.
• Configure, manage, and enhance Cortex Search indexes to enable intelligent enterprise document search and AI-assisted knowledge discovery.
• Develop AI-powered applications and assistants using Python, Snowpark, APIs, and Streamlit-in-Snowflake/ Integration with React.js frontEnd
• Lead migration and modernization of existing AI solutions into the Snowflake AI Data Cloud ecosystem.
• Implement document intelligence capabilities using Snowflake Document AI for extraction, classification, and knowledge retrieval from unstructured content.
• Snowpark Container Services (SPCS) deployment, management, and monitoring.
• Docker and containerization technologies.
• Python programming for data engineering and AI/ML workloads.
• Integration of Snowflake with APIs, enterprise applications, and data ingestion tools.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Snowflake security, RBAC, data access controls, and governance.
• Git-based source control and CI/CD pipeline implementation.
• Troubleshooting, production support, performance optimization, and cost management.
• Ability to design and deliver end-to-end data and AI solutions independently.
• Integrate AI solutions with enterprise data platforms, SharePoint repositories, APIs, and business applications.

Desirable Skills

• Kubernetes and container orchestration concepts to support advanced SPCS deployments.
• Knowledge of ML lifecycle management, model monitoring, and MLOps practices.
• Experience building end-to-end GenAI applications
• Understanding of vector databases, embeddings, and knowledge graph concepts.
• Experience with Infrastructure as Code (Terraform) and automated cloud deployments.
• Snowflake AI, SnowPro Advanced, or Cloud Platform certifications.

Qualifications:

• Experience: 2+ years in data engineering, AI/ML analytics, or application development using Snowflake and Python.
• Education: Bachelor’s or master’s degree in computer science, Data Science, Information Technology, or related field

Qualities:

Strong analytical and problem-solving mindset.

Ability to work effectively across multiple cloud platforms.

Excellent communication and stakeholder management skills.

Strong ownership and accountability for deliverables.

Adaptability to evolving technologies and business requirements.

Focus on solutioning, innovation, and continuous improvement.

Collaborative team player with a customer-focused approach.