Senior Data Architect

We are seeking an experienced Data Architect to lead the end-to-end architecture, design, and delivery of enterprise-scale Snowflake-based data platforms on Azure. This role will be responsible for defining target-state data architecture, driving large-scale migrations from legacy platforms, and establishing best practices for data modeling, ingestion, performance optimization, and cost governance. You will work closely with business and technical stakeholders while leading teams of data engineers to deliver scalable, secure, and high-performing analytics platforms. Key Responsibilities

Lead the end-to-end architecture and design of Snowflake data platforms on Azure, integrating with services such as Azure Data Factory (ADF), Synapse Pipelines, Azure Functions, Key Vault, and ADLS. Define and implement enterprise data modeling standards (Star/Snowflake schema, Dimensional Modeling, Data Vault) aligned to analytics, BI, and downstream data products. Design and govern secure, scalable, and cost-efficient Snowflake environments, including databases, schemas, roles, virtual warehouses, and resource monitors. Own the migration strategy and roadmap for moving data from on-prem / legacy data warehouses to Snowflake on Azure. Partner with stakeholders to assess current-state systems (source data, ETL, reporting, data quality) and define the target-state Snowflake architecture. Plan and execute migration waves and phases, including data profiling, schema conversion, historical and incremental loads, reconciliation, and cutover. Architect and oversee data ingestion pipelines from diverse sources (databases, flat files, APIs, streaming) into ADLS and Snowflake using ADF, Synapse, Databricks, and CDC patterns. Ensure data reconciliation, validation, and quality controls, delivering accuracy and performance parity or improvement over legacy platforms. Lead and mentor a team of data engineers and ETL developers, driving delivery across Snowflake migration and modernization initiatives. Define and enforce coding standards, code reviews, and CI/CD pipelines for Snowflake objects (SQL, views, stored procedures, streams, tasks). Design and implement ELT/ETL frameworks (staging → raw → curated → semantic layers) using tools such as dbt, ADF, Synapse, and Databricks. Implement automated testing and monitoring frameworks, including unit tests, regression tests, data quality checks, and SLA tracking. Monitor and optimize Snowflake query performance using profiling, clustering, partitioning, and warehouse sizing strategies. Drive cost optimization through auto-scaling, auto-suspend, resource monitors, and proactive Snowflake consumption management. Required Qualifications

8+ years of experience in Data Engineering, Data Warehousing, or Analytics. Deep understanding of enterprise data architecture, cloud-native data platforms, data security, access controls, and data governance principles. Proven experience leading at least one large-scale migration from on-prem or legacy platforms (e.g., Netezza, Yellowbrick, Oracle, SQL Server) to Snowflake on Azure. Strong expertise with Azure cloud services, including Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Azure Databricks and/or Azure Synapse Analytics, Azure Key Vault, and Azure DevOps or GitHub for CI/CD and source control. Proven ability to provide technical leadership, effectively communicate with business and technical stakeholders, and collaborate across cross-functional teams to drive data platform initiatives. Strong leadership, stakeholder communication, and cross-functional collaboration skills. Nice to Have

Experience with dbt for transformation and testing. Exposure to real-time or streaming data architectures. Experience in defining enterprise data governance and data quality frameworks.

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