Snowflake Data Engineer

Computing Concepts Inc; India; Remote; INR 2,500,000 - 3,500,000; Full time

Job summary

Computing Concepts Inc. is seeking a Snowflake Data Engineer to design, develop, and support enterprise data solutions on Snowflake for a remote 12+ month contract.

The role involves building scalable data pipelines, metadata-driven Frameworks, and automations, with responsibilities spanning both application and database domains. The ideal candidate has hands-on Snowflake development experience, strong SQL skills, and expertise with AWS Glue, S3, DMS, Liquibase, and CI/CD practices.

Qualifications

• 6+ years in data engineering with cloud data platforms.
• Hands-on Snowflake development and administration.
• Proficient in writing and optimizing SQL and Snowflake procedures.
• Experience with AWS Glue ETL and workflow orchestration.
• Experience with Liquibase for deployments.
• Experience with GitHub and CI/CD.
• Strong debugging and production support skills.

Responsibilities

• Design, develop, and maintain Snowflake data solutions.
• Build ETL/ELT pipelines for analytics workloads.
• Optimize query performance and resource utilization.
• Develop automation and metadata-driven frameworks.
• Support Snowflake platform administration tasks.
• Collaborate on deployment standards with teams.
• Develop AWS Glue jobs and data ingestion workflows.
• Manage data loads, quality, and monitoring.
• Create documentation and runbooks.

Skills

Strong troubleshooting

Excellent communication

Team collaboration

Problem solving

Root cause analysis

Tools

Snowflake

AWS Glue

Amazon S3

AWS DMS

Liquibase

GitHub

Python

Shell scripting

Aurora PostgreSQL

Job description

Role: Snowflake Data Engineer
Location: Remote

Contract/Fulltime: Contract, 12+ months - strong long-term extension potential

Shift Timings: Night Shift in India (6:30 PM to 3:30 AM IST)

Role Summary

We are seeking a skilled Snowflake Data Engineer to join our team. The ideal candidate will be responsible for designing, developing, deploying, and supporting enterprise data solutions on the Snowflake platform. This role involves building scalable data pipelines, developing metadata-driven frameworks, automating database deployments, and supporting production environments. The successful candidate will possess strong troubleshooting skills, be comfortable working across both application and database administration domains, and consistently produce well-documented, maintainable solutions.

Key Responsibilities

Snowflake Engineering & Development

• Design, develop, and maintain robust data solutions using Snowflake.
• Develop and support database objects including tables, views, streams, tasks, stored procedures, and dynamic SQL frameworks.
• Build scalable and performant ETL/ELT pipelines for data integration and analytics workloads.
• Optimize Snowflake query performance, storage utilization, and compute efficiency.
• Implement metadata-driven and configuration-based data processing frameworks.

Database Administration & Scripting

• Develop, support, and maintain database administration scripts for operational and support activities.
• Create automation scripts for database monitoring, housekeeping, deployments, validations, and health checks.
• Assist with Snowflake platform administration activities, including role management, access controls, warehouse management, and object security.
• Support operational automation across development, test, and production environments.
• Support Amazon Aurora PostgreSQL operational activities, including connectivity validation, performance troubleshooting, access coordination, and environment support.

Database Deployment & Release Management

• Utilize Liquibase for source-controlled database deployments and schema migrations.
• Develop and maintain deployment scripts and release automation processes.
• Ensure database changes are properly version-controlled, tested, and promoted through environments.
• Partner with development and operations teams to establish deployment standards and best practices.

Data Engineering & Operational Support

• Develop efficient data ingestion, transformation, and validation processes.
• Design, develop, and support AWS Glue jobs and workflows for data ingestion, transformation, cataloging, and orchestration across cloud and enterprise data platforms.
• Work with Amazon S3 for data landing, staging, archival, file organization, access patterns, and integration with Snowflake and AWS Glue pipelines.
• Support AWS Database Migration Service (AWS DMS) tasks for data replication, migration, validation, monitoring, and issue resolution across source and target platforms.
• Troubleshoot and resolve issues related to data pipelines, database performance, and application integrations.
• Perform root cause analysis and implement corrective actions for recurring issues.
• Monitor data loads, data quality processes, and platform performance to ensure reliability and availability.
• Support production incident management and operational escalations.

Software Engineering & Documentation

• Write clean, maintainable, and supportable code following engineering best practices.
• Design solutions with long-term maintenance, observability, and troubleshooting requirements in mind.
• Implement appropriate logging, exception handling, auditing, and monitoring capabilities.
• Produce comprehensive technical documentation for all solutions, processes, and deployments.
• Create and maintain operational runbooks, troubleshooting guides, architectural documentation, and knowledge transfer materials.
• Ensure all code deliveries are supplemented with proper and abundant documentation to support future maintenance and operational activities.

System Integration & DevOps

• Support CI/CD processes for database and data engineering solutions.
• Utilize GitHub for source code management, version control, and collaboration.
• Collaborate with application development, infrastructure, and data teams to deliver integrated enterprise solutions.
• Integrate Snowflake solutions with AWS services, including AWS Glue, Amazon Aurora PostgreSQL, Amazon S3, and AWS DMS, to support scalable enterprise data processing and interoperability.
• Participate in code reviews, deployment reviews, and technical design discussions.

Required Skills & Qualifications

• At least 6 years of relevant data engineering experience, including hands-on work with cloud data platforms and production data environments.
• Strong hands-on working experience with Snowflake development and administration.
• Proficiency in writing and optimizing complex SQL queries and Snowflake stored procedures.
• Hands-on proficiency with AWS Glue for ETL development, workflow orchestration, job monitoring, and troubleshooting.
• Experience developing database and application support scripts.
• Experience working with Amazon Aurora PostgreSQL, including SQL development, integration support, operational troubleshooting, and performance analysis.
• Experience working with Amazon S3 for storage, ingestion, staging, and integration with cloud-native data pipelines.
• Experience with AWS DMS for database migration, change data capture, replication monitoring, and troubleshooting.
• Hands-on experience with Liquibase for database deployment and schema version management.
• Strong troubleshooting, analytical, and problem-solving skills.
• Experience supporting production data warehouse or data platform environments.
• Ability to develop maintainable, reusable, and well-documented code.
• Experience with source control systems such as GitHub.
• Excellent verbal and written communication skills.
• Strong attention to detail and commitment to operational excellence.

Preferred Qualifications (Plus)

• Experience with cloud platforms such as AWS.
• Experience building cloud-native data pipelines using AWS Glue, Amazon Aurora PostgreSQL, Amazon S3, AWS DMS, Snowflake, and related AWS data services.
• Experience with Snowflake performance tuning and cost optimization.
• Experience implementing metadata-driven frameworks and data validation solutions.
• Proficiency with Python, Shell Scripting.
• Familiarity with CI/CD pipelines and DevOps practices.
• Knowledge of data warehousing concepts, dimensional modeling, and enterprise reporting platforms.
• Experience with monitoring, observability, and operational support frameworks.
• Experience supporting regulatory, audit, and data governance requirements.