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.
- Chance 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.

📌 Senior Snowflakes Data Warehouse Engineer - AWS QuickSight (Vadodara)
🏢 ALLIANZ CLOUD
📍 Vadodara