Senior Data Architect

Overview

Design & lead Azure‑based data solutions, pipelines, and governance for a cloud‑hybrid platform.

Key Responsibilities

• data pipelines
• data modeling
• azure databricks
• data governance
• api management
• data lake

Tasks

-Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks. -Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases. -Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform. -Implement data governance practices, including metadata management, data classification, and lineage tracking. -Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role-based access controls, encryption, and data masking. -Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud-native and hybrid environments. -Design and expose secure data services and APIs using Azure API Management for downstream systems. -Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts. -Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. -Provide technical leadership and mentorship to data engineers and analysts, promoting best practices in cloud data architecture and development. -Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance. -Collaborate with cross-functional teams to align data architecture with business requirements, program timelines, and modernization goals.

Requirements

• servicenow
• azure
• python
• databricks
• togaf
• talend

What You Bring

-Experience working with ServiceNow- Azure based Data Management Platform Integrations. -Use of AI-Experienced in using AI for code generation, data analysis, automation, and enhancing productivity in data engineering workflows. -Experience designing data solutions for analytics-ready, trusted datasets using tools like Power BI and Synapse, including semantic layers, data marts, and data products for self-service, data science, and reporting -Skilled in building secure, scalable RESTful APIs for data exchange, with robust auth, error handling, and support for real-time automation. -Experience in Python (including PySpark) and SQL, applied to developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in a large-scale cloud environment. -Experience working with cross-functional teams to create software applications and data products -Experience in data governance, security, and metadata management within a Databricks-based platform. -Experience building scalable ETL pipelines, data quality enforcement, and cloud integration using TALEND technologies. -Certification in The Open Group Architecture Framework (TOGAF). -Hands-on experience managing Databricks workspaces, including cluster configuration, user roles, permissions, cluster policies, and applying monitoring and cost optimization for efficient, governed Spark workloads -Experience in Message Queueing Technologies, implementing message queuing using tools like ActiveMQ and Service Bus for scalable, asynchronous communication across distributed systems. -Experience in Github/Git for version control, collaborative development, code management, and integration with data engineering workflows. -Experience with Azure services (Storage, SQL, Synapse, networking) for scalable, secure solutions, and with authentication (Service Principals, Managed Identities) for secure access in pipelines and integrations -Experience building scalable data pipelines with Azure Databricks, Delta Lake, Workflows, Jobs, and Notebooks, plus cluster management. Extending solutions to Synapse Analytics and Microsoft Fabric is a plus. -Direct, hands-on experience performing business requirement analysis related to data manipulation/transformation, cleansing and wrangling. -Experience as a Data Architect in a large enterprise, designing and implementing data architecture strategies and models that align data, technology, and business goals with strategic objectives -Experience and strong technical knowledge of Microsoft SQL Server, including database design, optimization, and administration in enterprise environments. -College or Bachelor degree in Computer Science or a related field of study.

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