Senior Snowflake Data Engineer

Algoleap Technologies; Hyderabad; On-site; INR 2,800,000 - 4,600,000; Full time

Job summary

Algoleap Technologies Pvt Ltd in Hyderabad is seeking a Senior Snowflake Data Engineer to design, develop, and maintain scalable data platform solutions supporting AI use cases. The role covers end-to-end data ingestion, modeling, and performance optimization for the Pacific Data Platform.

The ideal candidate will work with Snowflake Cortex AI, Cortex Analyst, and Cortex Search to enable natural-language analytics, intelligent search, and insights from structured and unstructured data.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.

Responsibilities

• Design and implement scalable Snowflake data architectures for storage, processing, reporting, analytics, and AI use cases.

Skills

Snowflake Data Engineering

SQL

Python programming

Data modeling

Data integration

Performance optimization

Data quality

Security

Education

Bachelor’s or Master’s degree in Computer Science / IT / Engineering

Tools

Snowpark

SnapLogic

Azure Data Factory

Snowflake Cortex AI

Cortex Analyst

Cortex Search

Job description

Algoleap Technologies Pvt Ltd | Full time

Job Title

Senior Snowflake Data Engineer –Data Platform & AI

JobLocation

Hyderabad

Experience

6–10 years

Start Date

As soon as possible

Role Overview

We are seeking a Senior Snowflake Data Engineer to design, develop, andmaintain scalable data platform solutions for the Pacific Data Platform. Therole 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, intelligentsearch, and insights from structured and unstructured data.

The successful candidate will work closely with cross-functional teams totranslate business requirements into reliable, secure, and cost-effectivesolutions. They should be self-directed and comfortable supporting the dataneeds 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, enterpriseapplications, and files, and prepare unstructured content for AI processing.
• Implement full-load, incremental-load, and change data capture processes withappropriate validation, reconciliation, and error handling.
• Develop and maintain dimensional and relational data models that accuratelyrepresent business requirements.
• Build and optimize tables, views, stored procedures, tasks, streams, anddynamic tables where appropriate.
• Analyze query profiles and optimize warehouse sizing, clustering, partitionpruning, 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 AIand 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 casesacross property, lease, availability, client, and market data.

Platform Operations and Collaboration

• Implement Snowflake role-based access control, masking policies, rowaccess 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 reliableproduction operations.
• Maintain version-controlled code and support automated deployments through Gitand Azure DevOps.
• Document architectures, data mappings, pipelines, semantic definitions, andoperational procedures.
• Collaborate with application engineers, analysts, architects, and business stakeholders throughout delivery.
• Mentor junior engineers and promote engineering standards, code reviews, andcontinuous improvement.

Key Qualifications

• Required Qualifications Bachelor’s ormaster’s degree in Computer Science, Information Technology, Engineering, or arelated 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, SQLdevelopment, performance optimization, and security.
• Advanced SQL skills, including complex joins, window functions, storedprocedures, query profiling, and troubleshooting.
• Strong Python programming skills for data processing, automation, APIintegration, and error handling.
• Experience with Snowpark for data transformations and application integration.
• Experience building pipelines using Azure Data Factory, or comparableintegration tools.
• Practical experience with Snowflake Cortex AI, Cortex Analyst, and CortexSearch.
• Ability to develop semantic views or semantic models with clear businessdefinitions 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 APIsor Python.