Senior Snowflakes Data Warehouse Engineer - AWS QuickSight

Allianz Cloud Pvt Ltd; United States; Remote; USD 110,000 - 150,000; Full time

Benefits offered by this job

Remote / Work-from-Home opportunity

Enterprise-scale Snowflake & AWS data‑

Multi-tenant data architecture & BI

Cross-functional collaboration

Contract extension opportunities

Job summary

Allianz Cloud Pvt Ltd in the United States is seeking a hands-on data engineer to own Snowflake migrations and scalable multi-tenant architectures for enterprise analytics. You will design, implement, and optimize data workflows using Snowflake, AWS Glue, Lambda, S3, and Step Functions to deliver secure BI dashboards with QuickSight.

You will enforce RBAC, encryption, and data governance, build IaC pipelines, and partner with product and engineering teams to ensure production-ready analytics.

Qualifications

• 8+? 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.

Responsibilities

• Lead migration of legacy SQL databases and data warehouse systems to Snowflake.
• Design scalable multi-tenant data warehouse architectures with 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 BI and enterprise reporting.
• Implement secure, role-based, multi-tenant analytics using QuickSight row-level security and Cognito integration.
• Optimise Snowflake query performance, compute usage, storage, and costs.
• Implement CI/CD pipelines and IaC using GitHub Actions, CodePipeline, Terraform, 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 analytics.
• Troubleshoot data pipelines and dashboards and maintain production reliability.

Skills

Snowflake architecture

Legacy data migrations

Multi-tenant design

Performance tuning

Advanced SQL

Data modelling

Query optimisation

AWS QuickSight

Dashboard development

AWS Glue

AWS Lambda

AWS S3

AWS Step Functions

IAM & encryption

Data governance

CI/CD

Infrastructure as Code

Terraform

AWS CDK

CloudFormation

Education

Bachelor’s or Master’s in Computer Science / IT / Engineering

Tools

Power BI

Tableau

Looker

Terraform

AWS CDK

CloudFormation

Job description

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.