Job Summary
The DRAS Data Product Analyst designs, develops, and operates trusted data products that support regulatory oversight, compliance monitoring, and evidence-based decision-making. This role uses Microsoft Azure services, Azure Databricks, Delta Lake, Python, PySpark, SQL, and Synapse Analytics to deliver secure, scalable, and analytics-ready datasets for the Digital Regulatory Assurance System. The position works closely with business, technical, and product stakeholders to ensure DRAS data assets are reliable, governed, and aligned with regulatory and operational priorities.

Key Responsibilities
• Work with business stakeholders, product owners, architects, and delivery teams to understand data product objectives, regulatory requirements, business needs, and success criteria.
• Design and implement scalable and secure Azure data solutions using Azure Storage, Azure SQL, Synapse Analytics, networking services, service principals, and managed identities.
• Develop, orchestrate, and optimize data ingestion and transformation pipelines using Azure Data Factory, Azure Databricks, Python, PySpark, SQL, and Delta Lake.
• Build and maintain Databricks Workflows, Jobs, Notebooks, clusters, and processing environments that support timely and reliable data operations.
• Design and curate standardized, high-quality data products, data marts, semantic layers, and analytics-ready datasets for regulatory reporting, compliance monitoring, self-service analytics, and future AI use cases.
• Monitor and troubleshoot data pipelines and data products, implementing data quality controls, error handling, security, governance, lineage, performance optimization, and operational support processes.
• Apply AI and automation tools to improve code development, data analysis, testing, documentation, monitoring, and continuous improvement across data engineering workflows.

Required Qualifications
• Minimum 9 years of relevant experience.
• Minimum 3 years of experience designing data solutions for trusted, analytics-ready datasets using tools such as Power BI and Synapse, including semantic layers, data marts, and data products.
• Minimum 4 years of experience using Git or GitHub for version control, collaborative development, code management, code review, and data engineering workflows.
• Minimum 3 years of experience using Azure services such as Storage, SQL, Synapse, and networking to build scalable and secure data solutions.
• Demonstrated experience securing Azure data pipelines and integrations using service principals, managed identities, role-based access, and appropriate authentication controls.
• Minimum 5 years of experience using Python, including PySpark, and SQL to develop, orchestrate, optimize, and troubleshoot enterprise-grade ETL/ELT workflows.
• Minimum 3 years of hands-on experience with Azure Databricks, Delta Lake, Workflows, Jobs, Notebooks, and cluster management.
• Minimum 1 year of experience using AI for code generation, data analysis, automation, productivity improvement, and data engineering workflow support.

Preferred Qualifications
• Minimum 6 years of experience performing business requirements analysis related to data manipulation, transformation, cleansing, and data wrangling.
• Minimum 6 years of experience with Microsoft SQL Server, including database design, optimization, and administration in enterprise environments.
• Experience with Microsoft Fabric and Azure Synapse Analytics, RESTful API integration, message queueing technologies such as ActiveMQ or Azure Service Bus, and cross-functional delivery of software applications and data products.