Senior Azure Engineer

Role Overview

As a Senior Azure Engineer (Remote, United States), you will translate analytics and platform needs into Azure-based data and integration architectures. You’ll lead solution design, deliver data platform capabilities, and help drive enterprise adoption of modern data solutions.

Responsibilities

• Translate functional requirements into technical designs and data solutions.
• Work with clients and internal stakeholders to understand data/platform requirements and determine the required Azure services.
• Architect Azure platform solutions to meet functional and non-functional requirements.
• Evaluate current technology landscapes and define forward-looking short- and long-term technology strategies.
• Create and share best practices, technical content, and reference architectures.
• Support RFP/RFI/RFQ responses.
• Oversee solution architecture and ensure standards are followed (modular, scalable codebase).
• Estimate effort using a parametric estimation model and align stakeholders on schedule and dependencies.
• Design, develop, and deliver:
  • Data integration interfaces using Azure Data Factory (ADF) and Azure Databricks.
  • Data provisioning interfaces to meet downstream consumption needs.
  • Data models on Azure (e.g., Azure Cosmos, Snowflake, Azure SQL Data Warehouse/Synapse).
• Advise clients on ML engineering and deploying MLOps at scale on AKS.
• Automate delivery activities to reduce lead time and improve quality.
• Optimize platform cost by selecting appropriate services and cost-effective architectures.
• Deploy Azure DevOps and CI/CD processes.
• Implement logging and monitoring across integration points for critical alerts.

Requirements

• 6–10 years of software development experience.
• Experience translating analytical requirements into technical designs, including data models, ETLs, and dashboards/reports.
• Experience deploying self-service analytics solutions on relational and non-relational databases.
• dbt (core or cloud) experience.
• Data Vault 2.0 implementation experience, including use of the automate_dv package.
• Experience with computing paradigms such as in-memory, distributed, MPP, and Unity Catalog.
• Delivered large-scale data management initiatives across Plan, Design, Build, Deploy, using Agile.
• Strong fundamentals in CI, static code analysis, and test-driven development.
• Experience delivering in a collaborative model with onsite and offshore teams.
• Excellent analytical/problem-solving skills.
• Experience delivering change management to drive data platform adoption across the enterprise.
• Experience working on APIs.
• Strong written and verbal communication skills; ability to work across internal/external organizations.

Azure Core Technologies (Required)

• Azure Data Lake Storage
• Azure Data Lake Analytics
• Azure Cosmos
• Azure Data Factory
• Snowflake
• Azure SQL Database
• Azure HDInsight
• Azure Databricks
• SQL Data Warehouse (Synapse)

Nice-to-Haves (Implied by Responsibilities)

• Experience supporting ML Ops deployments.
• Strong knowledge of platform cost optimization and observability (logging/monitoring).