Azure Data Architect

About the role

Azure Data Architect to lead the design and implementation of enterprise data ecosystem. The Data Architect will shape cloud data strategy, build robust data pipelines, and ensure data flows smoothly across storage, analytics, and reporting layers. Work with engineers, product managers, and business leaders to turn complex data needs into simple technical solutions.

Responsibilities

• Build secure, scalable, and cost-effective cloud data architectures using Azure services such as Azure Synapse Analytics, Azure Databricks, and Azure Data Lake Storage.
• Design and optimize batch and streaming ETL/ELT workflows using Azure Data Factory and Spark frameworks.
• Apply deep understanding of ETL/ELT processes, data warehousing principles, streaming/batch data processing, and data modeling.
• Create conceptual, logical, and physical data models for structured and unstructured data to support business intelligence and advanced analytics.
• Set up data governance, quality standards, and lineage tracking using tools like Microsoft Purview.
• Lead migration of legacy on‑premises or Azure databases and data warehouses to Azure or GCP with minimal downtime, including re‑architecture of legacy data warehouses.
• Implement strict access controls, data masking, and role‑based security using Azure Active Directory and Key Vault.
• Provide technical guidance and best practices to data engineering and development teams.
• Monitor, troubleshoot, and optimize data storage, cost efficiency, and high‑performance query execution in BigQuery and other database layers.

Requirements

• Must‑have: Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure; strong proficiency in Python or Scala for data processing.
• Good‑to‑have: Snowflake, Kafka/Event Hub, Power BI, Machine Learning integration on Azure, Terraform or Infrastructure as Code (IaC).
• Hands‑on design experience with BigQuery, Dataflow, Dataproc, Cloud Storage, and Cloud SQL/Spanner.
• Experience with relational and dimensional data modeling.
• Experience implementing data governance, quality standards, and lineage tracking.

Benefits

• Discretionary Annual Incentive
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans
• Family Support: Maternal & Parental Leaves
• Insurance Options: Auto & Home Insurance, Identity Theft Protection
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement
• Time Off: Vacation, Sick Leave & Holidays
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing

Pay