Senior Snowflakes Data Warehouse Engineer - AWS QuickSight

Role & responsibilities

• Lead migration of legacy SQL databases and data warehouse systems to Snowflake.
• Design scalable multi-tenant data warehouse architectures with appropriate tenant isolation, RBAC, and resource governance.
• Develop, maintain, and optimise SQL queries, data models, and ETL/ELT pipelines.
• Build automated data ingestion and transformation workflows using AWS Glue, Lambda, S3, and Step Functions.
• Design and deploy AWS QuickSight dashboards for business intelligence and enterprise customer reporting.
• Implement secure, role-based, multi-tenant analytics using QuickSight row-level security and Amazon Cognito integration.
• Optimise Snowflake query performance, compute utilisation, storage, and operating costs.
• Implement CI/CD pipelines and Infrastructure-as-Code using GitHub Actions, AWS CodePipeline, Terraform, AWS CDK, or CloudFormation.
• Apply security controls covering IAM, encryption, audit logging, and data governance.
• Collaborate with product, engineering, and business stakeholders to translate reporting requirements into reliable analytics solutions.
• Troubleshoot complex data pipeline and dashboard issues and maintain production reliability.

Preferred candidate profile

Essential Requirements

• 812 years of relevant experience in data engineering, data warehousing, or analytics engineering.
• Strong production experience with Snowflake architecture, legacy data migrations, multi-tenancy, and performance tuning.
• Advanced SQL, data modelling, and query optimisation skills.
• Hands-on AWS QuickSight experience, including dashboard development, row-level security, and secure customer-facing analytics.
• Experience with AWS Glue, Lambda, S3, and Step Functions.
• Practical understanding of identity and access management, tenant isolation, encryption, and data governance.
• Experience with CI/CD and Infrastructure-as-Code practices.

Preferred Skills

• Amazon Cognito integration with analytics applications.
• Kimball methodology, Data Vault, Star Schema, and Snowflake Schema.
• Terraform, AWS CDK, or CloudFormation.
• Power BI, Tableau, or Looker.
• Kafka, Amazon Kinesis, or real-time analytics.
• Telecom, wireless, networking, or network telemetry data.
• AI/ML-driven analytics.

Ideal Candidate

We are looking for a hands-on engineer who can independently own complex Snowflake migration and architecture assignments, implement secure multi-tenant analytics, and deliver production-ready AWS QuickSight solutions.

Candidates must be comfortable working remotely, collaborating across teams, and communicating technical decisions clearly.

Relevant bachelor’s or master’s qualifications in Computer Science, IT, Engineering, or a related field are preferred. Strong practical experience is essential.

Perks and benefits

• Remote / Work-from-Home opportunity across India.
• Opportunity to work on enterprise-scale Snowflake and AWS data engineering projects.
• Exposure to multi-tenant data architecture, cloud analytics, and secure customer-facing BI solutions.
• Opportunity to collaborate with cross-functional engineering teams and enterprise stakeholders.
• Contract extension or future engagement opportunities may be considered based on project requirements and performance.

Compensation: Negotiable based on relevant experience, technical expertise, and project suitability.

Contract duration, working hours, and any additional benefits will be communicated during the selection process.