Snowflake Data Engineer (AWS)

Key Responsibilities

• Design, develop, test, and maintain ETL/ELT pipelines using Snowflake, AWS, Python, and PySpark.
• Integrate Snowflake with AWS services, including S3, IAM, Lambda, Glue, SNS/SQS, and Step Functions.
• Develop and manage Snowflake objects such as Snowpipe, Streams, Tasks, stages, storage integrations, and external/Iceberg tables.
• Perform data migration from on-premises systems, Hadoop/Hive, and legacy data warehouses to Snowflake.
• Write complex SQL queries and optimize query performance, warehouse utilization, and data processing.
• Implement secure data access using Snowflake RBAC, AWS IAM, KMS, and other relevant cloud security mechanisms.
• Collaborate with Subject Matter Experts (SMEs), Business Analysts, developers, and business stakeholders to understand requirements and deliver data solutions.
• Troubleshoot data pipeline failures, cloud permissions, networking issues, and production incidents.
• Support technical implementations, ongoing maintenance, and platform stability.
• Use Git, Bitbucket, and other source control tools to manage code.
• Support CI/CD and Infrastructure-as-Code practices for reliable deployments.

Mandatory Skills and Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent experience.
• 4–6 years of overall IT experience.
• Minimum 2 years of hands-on experience in Snowflake Data Engineering.
• Strong hands-on experience with AWS services:
• Amazon S3
• AWS IAM
• AWS Lambda
• AWS Glue
• Amazon SNS/SQS
• AWS Step Functions
• AWS KMS
• Amazon CloudWatch
• Strong programming experience in Python and PySpark, with experience delivering multiple projects.
• Advanced SQL skills, including window functions, semi-structured data processing, and query performance tuning.
• Hands-on experience with Snowflake Snowpipe, Streams, Tasks, stages, storage integrations, RBAC, and warehouse optimization.
• Experience with Git, Bitbucket, or other source code management tools.
• Understanding of cloud security, data integration, and scalable data pipeline architecture.
• Previous experience working with MNCs.
• Must be a local candidate from Delhi NCR and available to work onsite in Gurgaon.

Technical Skills

Snowflake

• Snowpipe, Streams, and Tasks
• Snowpark
• External and Iceberg tables
• Role-Based Access Control (RBAC)
• Warehouse and query optimization

AWS

• S3, IAM, Lambda, Glue
• SNS/SQS and Step Functions
• KMS and CloudWatch
• VPC and PrivateLink

Programming and Data Processing

• Python
• PySpark
• Advanced SQL
• ETL/ELT pipeline development

DevOps and Deployment

• Git and Bitbucket
• Jenkins
• Terraform and CloudFormation
• dbt
• Ansible

Data Migration

• Hadoop
• Hive
• Legacy data warehouses

Scheduling Tools

• Zeke
• AutoSys

Good-to-Have Skills

• Experience with Terraform, CloudFormation, Jenkins, Ansible, or other DevOps and Infrastructure-as-Code tools.
• Knowledge of dbt and schema change management for Snowflake deployments.
• Experience migrating Hadoop/Hive workloads or legacy data warehouses to Snowflake.
• Exposure to Snowflake Snowpark and external/Iceberg tables.
• Experience with Informatica IDMC.
• Familiarity with Zeke, AutoSys, or similar scheduling tools.
• Snowflake SnowPro Core or AWS certifications.
• Insurance industry experience, preferably involving multiple clients.
• Experience working in a global delivery environment.

Candidate Eligibility Requirements

Candidates must meet the following criteria:

• 4–6 years of overall IT experience.
• At least 2 years of hands-on Snowflake Data Engineering experience.
• Previous MNC experience.
• Must be based locally in Delhi NCR.
• Must be willing to work onsite in Gurgaon.
• Must be an immediate joiner or serving a notice period of no more than 15 days.
• Must be available for two virtual interview rounds.

Pay: ₹1,100,000.00 - ₹1,500,000.00 per year

Application Question(s):

• By applying, you agree that your resume and personal details may be stored securely for up to 2 years for recruitment purposes.

Work Location: Hybrid remote in Gurgaon, Haryana 122022