Data Architect

The Data Architects, under the working job title of Extract, Transform, Load (ETL) Architects, will serve

as the principal line of communication for the project team. The ETL Architects will drive the development

of data integration pipelines, enabling efficient, reliable access to critical data within the Correction

Information Management System (CIMS) Data Warehouse/Data Lake on Azure. They will

work with Azure Data Factory (ADF), Azure Databricks, Azure Synapse, Power BI, and Azure Purview.

The ETL Architects will be at the forefront of transforming complex data into actionable insights. The ETL

Architects will be responsible for ensuring data integrity, security, and performance, all while

meeting mission-critical needs. The specific duties and responsibilities of this position are as follows:

ETL Pipeline Design and Development:

• Lead the design and development of high-performing ETL processes to integrate and transform data across disparate sources;

• Deliver efficient, reliable pipelines that meet business needs and maintain the highest standards of security; and

• Utilize ADF to automate and streamline data workflows, ensuring smooth transitions from source to target.

Data Integration and Transformation:

• Build and manage complex ETL workflows that extract, transform, and load data for downstream analytics and reporting, ensuring data is accurate, timely, and secure; and

• Take ownership of data quality and validation, creating resilient ETL processes that ensure only trusted data reaches its destination.

Cloud Platform Expertise:

• Leverage the full power of the Azure ecosystem—ADF, Databricks, Synapse, and Purview—to manage and process high volumes of structured and unstructured data, delivering solutions that are scalable and performance-optimized; and

• Integrate large datasets into Azure Synapse Analytics, enabling analytics teams to deliver data-driven insights that support the Department's mission.

Performance Optimization:

• Continuously optimize ETL jobs to minimize latency and maximize throughput; and

• Ensure the architecture supports fast, reliable data access for end-users and systems, meeting stringent performance metrics.

Security and Compliance:

• Embed security and compliance best practices in every step of the ETL process;.

• Protect sensitive data by adhering to industry standards and ensuring compliance with the Department's data governance policies; and

• Use Azure Purview to enforce data governance, track data lineage, and ensure that data handling meets the highest standards of integrity.

Collaboration and Stakeholder Engagement:

• Partner with cross-functional teams (e.g., data engineers, analysts, business stakeholders, and security experts) to design and implement ETL solutions that meet the Department's evolving needs; and

• Act as a technical leader and mentor, helping guide junior team members and providing expert guidance on data processing and transformation best practices

Documentation and Best Practices:

• Develop and maintain clear, detailed documentation for ETL processes, ensuring the team can consistently deliver high-quality, reliable solutions; and

• Establish and enforce best practices for data handling, ETL development, and security, driving a culture of excellence and accountability.

Required Qualifications

A bachelor's degree from an accredited college or university in Computer Science, Information Systems, or a related field is required. Alternatively, equivalent work experience, including experience in Service-Oriented Architecture (SOA) and Microsoft Azure Cloud Solutions, can be substituted for the educational requirement on a year-for-year basis, when applicable.

The Department requires the following experience, skills, and knowledge for this position:

• Seven (7) or more years of experience in ETL development and data engineering;

• Three (3) or more years of hands-on experience working with ADF, Azure Cloud, Azure Databricks, Azure Synapse Analytics, and Azure Purview;

• Proven track record of building and optimizing large-scale ETL pipelines for high-performance, high-availability environments;

• Extensive expertise in Spark, Python, and/or Scala for large-scale data transformations;

• Strong Structured Query Language (SQL) proficiency and experience working with complex data structures;

• In-depth knowledge of data governance, security protocols, and role-based access control (RBAC) within the Azure ecosystem; and

• Ability to design ETL processes that are resilient, efficient, and fully compliant with regulatory standards.