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Job DescriptionPosition Summary
Lead the Azure pillar within the Data Engineering CoE, establishing technical standards, best practices, and
reusable accelerators for Azure data platform implementations. This role will directly support high-value
opportunities in our pipeline
Key Responsibilities
Develop architecture patterns and implementation accelerators for Azure data platforms
Establish best practices for Azure Synapse, Data Factory, Azure Databricks, and other Azure data
services
Support pre-sales activities for Azure-based opportunities, particularly AIMajodouie and Anthology
Design migration pathways from legacy systems to Azure
Create technical documentation and playbooks for Azure implementations
Mentor junior team members on Azure best practices
Work with cloud-agnostic platforms (Databricks, Snowflake) in Azure environments
Collaborate with other pillar architects on cross-platform solutions
Build customer relationships as a trusted technical advisor for Azure implementations
10+ years of data engineering experience with 5+ years focused on Azure
Deep expertise in Azure Synapse Analytics, Azure Data Factory, and Azure Databricks
Experience with Azure data lake implementations (ADLS Gen2)
Strong knowledge of data integration patterns and ETL/ELT frameworks
Experience with migration from legacy systems to Azure
Microsoft certified Azure Data Engineer Associate or higher
Experience developing reusable templates and accelerators
Strong coding skills in Python, Spark, and SQL
Experience with Azure DevOps, ARM templates, or other infrastructure as code approaches
Excellent communication skills and client-facing experience
Technical Stack:
Azure Core Services: Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage Gen2
Data Warehouse: Azure Synapse Analytics, Azure SQL Database
Data Processing: Azure Databricks, Synapse Spark, Azure HDInsight
ETL/ELT: Azure Data Factory, Synapse Pipelines, Azure Databricks notebooks
Orchestration: Azure Data Factory, Logic Apps
Streaming: Event Hubs, Stream Analytics
ML Integration: Azure Machine Learning, Azure Databricks ML
Languages: Python, SQL, Scala, .NET
DevOps: Azure DevOps, GitHub Actions
Infrastructure as Code: Bicep, ARM Templates, Terraform
Monitoring: Azure Monitor, Application Insights
Certifications: Microsoft Certified: Azure Data Engineer Associate, Azure Solutions Architect
Impact Expectations
Create 2-3 Azure accelerators for common implementation patterns in the first 90 days
Develop technical proposal components for Azure-based opportunities
Establish Azure architecture frameworks aligned with Microsoft best practices
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What We Do
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Sutherland is an experience-led digital transformation company. Our mission is to deliver exceptionally engineered experiences for customers and employees today, that continue to delight tomorrow.
For over 35 years, we have cared for our customers’ customers, delivering measurable results and accelerating growth. Our proprietary, AI-based products and platforms are built using robust IP and automation.
We are a team of global professionals, operationally effective, culturally meshed, and committed to our clients and to one another.
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