The Role
Design and maintain scalable Snowflake data platforms, including ingestion, transformation, modeling, optimization, security, data quality, and production operations. Build ETL/ELT pipelines with SQL, Python, Snowpark, and Azure Data Factory. Develop AI-enabled solutions using Snowflake Cortex AI, Cortex Analyst, Cortex Search, semantic models, embeddings, and RAG. Collaborate with stakeholders, implement governance and monitoring, support deployments, document solutions, and mentor junior engineers.
Summary Generated by Built In
Job Title: Senior Snowflake Data Engineer –
Data Platform & AI
Job Location: Hyderabad
Experience: 6–10 years
Start Date: As soon as possible
Role Overview
We are seeking a Senior Snowflake Data Engineer to design, develop, and maintain scalable data platform solutions for the Pacific Data Platform. The role covers end-to-end data ingestion, transformation, data modeling, performance optimization, security, and data quality.
The role also involves developing AI-enabled solutions using Snowflake Cortex AI, Cortex Analyst, and Cortex Search to support natural-language analytics, intelligent search, and insights from structured and unstructured data.
The successful candidate will work closely with cross-functional teams to translate business requirements into reliable, secure, and cost-effective solutions. They should be self-directed and comfortable supporting the data needs of multiple teams, systems, and products.
Key Responsibilities
Snowflake Data Engineering
Design and implement scalable Snowflake data architectures for storage, processing, reporting, analytics, and AI use cases and strong sql,
Develop and maintain ETL/ELT pipelines using SQL, Python, Snowpark, SnapLogic, and/or Azure Data Factory.
Integrate structured and semi-structured data from databases, APIs, enterprise applications, and files, and prepare unstructured content for AI processing.
Implement full-load, incremental-load, and change data capture processes with appropriate validation, reconciliation, and error handling.
Develop and maintain dimensional and relational data models that accurately represent business requirements.
Build and optimize tables, views, stored procedures, tasks, streams, and dynamic tables where appropriate.
Analyze query profiles and optimize warehouse sizing, clustering, partition pruning, and caching to improve performance and control costs.
Review existing SQL and Python code to improve efficiency, security, robustness, and maintainability.
Implement data quality checks for completeness, accuracy, consistency, validity, and duplication.
Snowflake AI and Cortex
Design and implement AI-enabled data solutions using Snowflake Cortex AI and Snowpark, Cortex Analyst, Cortex Search and Agent creation
Apply Cortex AI functions to relevant use cases such as text summarization, classification, information extraction, and data enrichment.
Collaborate with business stakeholders to identify practical AI use cases across property, lease, availability, client, and market data.
Platform Operations and Collaboration
Implement Snowflake role-based access control, masking policies, row access policies, and auditing in line with enterprise security requirements.
Monitor pipeline execution, data freshness, warehouse utilization, failures, and service performance.
Establish logging, alerting, retry, and recovery mechanisms for reliable production operations.
Maintain version-controlled code and support automated deployments through Git and Azure DevOps.
Document architectures, data mappings, pipelines, semantic definitions, and operational procedures.
Collaborate with application engineers, analysts, architects, and business stakeholders throughout delivery.
Mentor junior engineers and promote engineering standards, code reviews, and continuous improvement.
Key Qualifications
Required Qualifications
Bachelor’s or master’s degree in Computer Science, Information Technology, Engineering, or a related field.
6–10 years of relevant experience in data engineering, database development, or cloud data platforms.
Strong hands-on experience with Snowflake architecture, data loading, SQL development, performance optimization, and security.
Advanced SQL skills, including complex joins, window functions, stored procedures, query profiling, and troubleshooting.
Strong Python programming skills for data processing, automation, API integration, and error handling.
Experience with Snowpark for data transformations and application integration.
Experience building pipelines using Azure Data Factory, or comparable integration tools.
Practical experience with Snowflake Cortex AI, Cortex Analyst, and Cortex Search.
Ability to develop semantic views or semantic models with clear business definitions and validated analytical queries.
Understanding of natural-language-to-SQL, semantic and keyword search, embeddings, text chunking, and RAG.
Experience integrating Snowflake AI capabilities with applications using APIs or Python.
Job Location: Hyderabad
Experience: 6–10 years
Start Date: As soon as possible
Role Overview
We are seeking a Senior Snowflake Data Engineer to design, develop, and maintain scalable data platform solutions for the Pacific Data Platform. The role covers end-to-end data ingestion, transformation, data modeling, performance optimization, security, and data quality.
The role also involves developing AI-enabled solutions using Snowflake Cortex AI, Cortex Analyst, and Cortex Search to support natural-language analytics, intelligent search, and insights from structured and unstructured data.
The successful candidate will work closely with cross-functional teams to translate business requirements into reliable, secure, and cost-effective solutions. They should be self-directed and comfortable supporting the data needs of multiple teams, systems, and products.
Key Responsibilities
Snowflake Data Engineering
Design and implement scalable Snowflake data architectures for storage, processing, reporting, analytics, and AI use cases and strong sql,
Develop and maintain ETL/ELT pipelines using SQL, Python, Snowpark, SnapLogic, and/or Azure Data Factory.
Integrate structured and semi-structured data from databases, APIs, enterprise applications, and files, and prepare unstructured content for AI processing.
Implement full-load, incremental-load, and change data capture processes with appropriate validation, reconciliation, and error handling.
Develop and maintain dimensional and relational data models that accurately represent business requirements.
Build and optimize tables, views, stored procedures, tasks, streams, and dynamic tables where appropriate.
Analyze query profiles and optimize warehouse sizing, clustering, partition pruning, and caching to improve performance and control costs.
Review existing SQL and Python code to improve efficiency, security, robustness, and maintainability.
Implement data quality checks for completeness, accuracy, consistency, validity, and duplication.
Snowflake AI and Cortex
Design and implement AI-enabled data solutions using Snowflake Cortex AI and Snowpark, Cortex Analyst, Cortex Search and Agent creation
Apply Cortex AI functions to relevant use cases such as text summarization, classification, information extraction, and data enrichment.
Collaborate with business stakeholders to identify practical AI use cases across property, lease, availability, client, and market data.
Platform Operations and Collaboration
Implement Snowflake role-based access control, masking policies, row access policies, and auditing in line with enterprise security requirements.
Monitor pipeline execution, data freshness, warehouse utilization, failures, and service performance.
Establish logging, alerting, retry, and recovery mechanisms for reliable production operations.
Maintain version-controlled code and support automated deployments through Git and Azure DevOps.
Document architectures, data mappings, pipelines, semantic definitions, and operational procedures.
Collaborate with application engineers, analysts, architects, and business stakeholders throughout delivery.
Mentor junior engineers and promote engineering standards, code reviews, and continuous improvement.
Key Qualifications
Required Qualifications
Bachelor’s or master’s degree in Computer Science, Information Technology, Engineering, or a related field.
6–10 years of relevant experience in data engineering, database development, or cloud data platforms.
Strong hands-on experience with Snowflake architecture, data loading, SQL development, performance optimization, and security.
Advanced SQL skills, including complex joins, window functions, stored procedures, query profiling, and troubleshooting.
Strong Python programming skills for data processing, automation, API integration, and error handling.
Experience with Snowpark for data transformations and application integration.
Experience building pipelines using Azure Data Factory, or comparable integration tools.
Practical experience with Snowflake Cortex AI, Cortex Analyst, and Cortex Search.
Ability to develop semantic views or semantic models with clear business definitions and validated analytical queries.
Understanding of natural-language-to-SQL, semantic and keyword search, embeddings, text chunking, and RAG.
Experience integrating Snowflake AI capabilities with applications using APIs or Python.
Skills Required
- Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or a related field
- 6-10 years of relevant experience in data engineering, database development, or cloud data platforms
- Hands-on experience with Snowflake architecture, data loading, SQL development, performance optimization, and security
- Advanced SQL skills, including complex joins, window functions, stored procedures, query profiling, and troubleshooting
- Strong Python programming skills for data processing, automation, API integration, and error handling
- Experience with Snowpark for data transformations and application integration
- Experience building pipelines using Azure Data Factory or comparable integration tools
- Practical experience with Snowflake Cortex AI, Cortex Analyst, and Cortex Search
- Ability to develop semantic views or semantic models with clear business definitions and validated analytical queries
- Understanding of natural-language-to-SQL, semantic and keyword search, embeddings, text chunking, and RAG
- Experience integrating Snowflake AI capabilities with applications using APIs or Python
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The Company
What We Do
AlgoLeap specializes in AI-powered software solutions, digital product engineering, and IT consulting services, focusing on digital transformation and AI-driven innovation.
