Position Overview

We are looking for an experienced Snowflake Data Engineer to join our data team and contribute to the design, implementation, and support of modern enterprise data platforms. This role will focus on developing scalable data solutions within Snowflake, building and optimizing data pipelines, automating deployment processes, and ensuring stable production operations. The ideal candidate will have strong expertise across data engineering and database administration functions, along with excellent problem-solving skills and a commitment to delivering well-documented, supportable solutions.

Primary ResponsibilitiesSnowflake Development & Data Solutions

- Architect, build, and maintain enterprise-grade data solutions leveraging Snowflake.
- Create and support database components including tables, views, streams, tasks, stored procedures, and dynamic SQL-based solutions.
- Develop scalable ETL/ELT processes to support analytics, reporting, and data integration initiatives.
- Improve query performance, storage utilization, and overall platform efficiency within Snowflake.
- Design and implement metadata-driven and configuration-based processing frameworks to enhance scalability and maintainability.

Database Operations & Automation

- Develop and maintain administrative scripts to support database operations and monitoring activities.
- Automate routine tasks including health checks, environment validation, deployments, monitoring, and housekeeping functions.
- Assist with Snowflake administration activities such as security management, access controls, role assignments, and warehouse configuration.
- Support operational processes across development, QA, and production environments.
- Provide operational support for Amazon Aurora PostgreSQL environments, including connectivity validation, performance investigations, user access coordination, and system support.

Release Management & Database Deployments

- Manage schema changes and database deployments using Liquibase in a source-controlled environment.
- Build and maintain automated release and deployment processes.
- Ensure database changes are appropriately versioned, tested, and promoted through multiple environments.
- Work closely with engineering and operations teams to establish deployment standards and governance practices.

Data Engineering & Production Support

- Develop and maintain data ingestion, transformation,



and validation solutions.
- Design and support AWS Glue jobs and workflows for data movement, transformation, catalog management, and orchestration.
- Utilize Amazon S3 for data storage, staging, archival, and integration with Snowflake and AWS-based pipelines.
- Support AWS DMS activities involving data replication, migration, monitoring, validation, and troubleshooting.
- Investigate and resolve issues related to pipeline failures, database performance, and application integrations.
- Perform root cause analysis and implement long-term corrective measures.
- Monitor system performance, data quality, and data processing activities to ensure platform reliability.
- Participate in production support activities, including incident response and operational escalations.

Engineering Standards & Documentation

- Develop high-quality, maintainable, and reusable code following established engineering practices.
- Design solutions with a focus on operational support, observability, monitoring, and long-term sustainability.
- Implement effective logging, auditing, monitoring, and exception-management capabilities.
- Create and maintain technical documentation covering architecture, deployments, workflows, and operational procedures.
- Prepare support runbooks, troubleshooting guides, and knowledge transfer materials.
- Ensure every solution is delivered with comprehensive documentation to support future maintenance and operations.

DevOps & System Integration

- Support CI/CD practices for database and data engineering deployments.
- Utilize GitHub and other source control tools for version management and collaboration.
- Partner with infrastructure, application, and data teams to deliver integrated enterprise solutions.
- Integrate Snowflake with AWS services including AWS Glue, Amazon Aurora PostgreSQL, Amazon S3, and AWS DMS to enable scalable data processing capabilities.
- Participate in technical reviews, code reviews, deployment assessments, and solution design discussions.





Required Qualifications

- Minimum 6 years of experience in data engineering, cloud-based data platforms, and production data environments.
- Strong hands-on expertise in Snowflake development and platform administration.
- Advanced SQL skills with experience developing and optimizing complex queries and stored procedures.
- Experience building and supporting AWS Glue ETL jobs, workflow orchestration, monitoring, and troubleshooting.
- Experience developing automation, database administration, or application support scripts.
- Hands-on experience with Amazon Aurora PostgreSQL, including SQL development, operational support, troubleshooting, and performance tuning.
- Experience utilizing Amazon S3 for data storage, ingestion, staging, and cloud data pipeline integration.
- Working knowledge of AWS DMS for data migration, CDC implementation, monitoring, and issue resolution.
- Experience using Liquibase for schema management, version control, and deployment automation.
- Robust analytical, troubleshooting, and problem-solving abilities.
- Experience supporting enterprise data warehouse or large-scale data platform environments.
- Ability to write reusable, maintainable, and thoroughly documented code.
- Experience with GitHub or other source control repositories.
- Excellent written and verbal communication skills.
- Strong attention to detail along with a commitment to operational excellence.

Preferred Qualifications

- Experience working within AWS cloud environments.
- Hands-on experience designing cloud-native data solutions utilizing Snowflake, AWS Glue, Amazon Aurora PostgreSQL, Amazon S3, AWS DMS, and related AWS technologies.
- Knowledge of Snowflake performance optimization and cost-management strategies.
- Experience building metadata-driven architectures and data quality validation frameworks.
- Proficiency in Python and Shell scripting.
- Familiarity with CI/CD methodologies and DevOps best practices.
- Understanding of data warehousing concepts, dimensional modeling techniques, and enterprise reporting solutions.
- Experience with monitoring platforms, observability tools, and operational support frameworks.
- Knowledge of regulatory compliance, audit processes, and data governance standards.

SNOWFLAKE AND AWS SKILLSETS ARE NEEDED

CONTACT KHURRAM AT khurram"at"khoj-inc.com

Work Location: Remote

📌 Snowflake Data Engineer (India)
🏢 Khoj Information Technology
📍 India