Principal Data Solutions Architect

Principal Data Solutions Architect

The Data Solutions Architect will be responsible for developing and leading the design of robust data architectures that align with business objectives and support data-driven decision-making across the organization. This role is focused on creating scalable, high-performance data solutions that integrate data from multiple sources, ensuring that it is accessible, consistent, and secure. By utilizing modern data technologies and platforms, the Data Solutions Architect will enable data sharing across various business functions and ensure that data is transformed into valuable insights for both operational and strategic purposes. This position will involve working closely with cross-functional teams to understand business requirements, assess existing systems, and design architectures that meet both current and future needs. The Data Solutions Architect will play a key role in driving innovation by introducing best practices in data management, governance, and analytics. They will also contribute to the continuous improvement of data processes, ensuring that the solutions developed are flexible, sustainable, and aligned with the organization's broader technology roadmap. The successful candidate will have a strong technical background, with a deep understanding of cloud-based data platforms, integration technologies, and data governance. They will collaborate with IT, business, and leadership teams to ensure that the data architecture supports business priorities while optimizing performance, security, and cost efficiency. Additionally, this individual will provide mentorship and guidance to junior team members and contribute to the overall evolution of the company's data strategy.

Primary Duties and Accountabilities

• Design and implement scalable data architectures, including conceptual, logical, and physical models, to meet business objectives and support data-driven decision-making across the organization.
• Lead the development and optimization of data pipelines and data warehousing solutions, ensuring data accuracy, consistency, and accessibility for reporting and business intelligence.
• Collaborate with business and IT teams to translate business needs into comprehensive data solutions, aligning them with strategic goals while maintaining high data quality, integrity, and security.
• Establish and enforce data governance practices to ensure compliance with regulatory standards and industry best practices, while fostering a culture of data stewardship and responsibility.
• Stay informed about emerging data technologies, tools, and trends, recommending and implementing innovative solutions to enhance organizational data capabilities and business insights.
• Mentor and guide cross-functional teams in the design and implementation of scalable solutions including data platforms that deliver actionable insights for business users, while supporting the growth and development of data teams.
• Continuously review and optimize existing data systems, identifying opportunities for improvement in efficiency, performance, and user satisfaction, while mitigating potential risks and ensuring project success.
• Communicate data strategies and complex technical concepts effectively to both technical and non-technical stakeholders, ensuring alignment with business needs and fostering strong collaboration across teams.
• Promote a data-driven culture by educating stakeholders on best practices for data management, reporting tools, and leveraging data insights to support strategic business decisions.
• Ensure all data solutions adhere to enterprise architecture frameworks, promoting consistency, scalability, and ongoing development while supporting the growth and development of data teams.

Minimum Qualifications

• Bachelor's degree in Information Systems with 8-years experience, in lieu of degree 12-years experience
• 10-years experience in IT with at least 5-years in data architecture, data engineering, or similar role
• Hands-on experience with Microsoft Azure services, including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and other Azure data components
• Proven expertise in designing and delivering large-scale data solutions
• Extensive expertise in data architecture, including data modeling, ETL pipelines, data lakes, and business intelligence solutions, with proficiency in Big Data technologies (e.g., Hadoop, Spark, Kafka) and both relational and NoSQL databases (e.g., SQL Server, MongoDB), along with a strong understanding of Data Lake, Data Mart, DataMesh, and Data Hub concepts
• Proficiency in data modeling for both OLTP and OLAP systems, and familiarity with data formats such as Avro and Parquet
• Ability to define enterprise-level data standards and contribute to the selection of appropriate tools
• Solid understanding of data governance, data security best practices, and cybersecurity fundamentals in the context of cloud-based and enterprise data systems
• Experience in data profiling and data cataloging to ensure high-quality, well-structured data
• Ability to maintain up-to-date Data Dictionaries in a disciplined manner
• Hands-on experience with data modeling tools such as Erwin, Power Designer, or similar platforms for creating and managing complex data models
• Ability to analyze functional and non-functional business requirements and translate them into scalable technical data solutions
• Proven ability to lead cross-functional teams, manage large-scale projects, and collaborate with senior leadership to define and align data strategies with business goals
• Excellent communication skills (written and verbal) for conveying complex findings to non-technical stakeholders
• Strong negotiation, analytical, communication skills and vendor relations

Preferred Qualifications

• Master's degree or other advanced technical discipline degree
• Experience with MLOps tools like Azure Machine Learning or MLFlow
• Expertise in optimizing Azure data solutions for performance, scalability, and cost-efficiency, including performance tuning and troubleshooting complex data systems
• Familiarity with data governance best practices, including data privacy laws (e.g., GDPR, CCPA), and the ability to ensure data security through encryption, access controls, and auditability