Principal Data Architect

Drive the adoption of best practices in data architecture, data modeling, and data engineering processes with a focus on enterprise reuse, developer experience, innovation, and productivity.,Collaborate closely with stakeholders, solution architects, data scientists, and engineering teams to understand data needs, propose solutions, and ensure alignment with strategic goals.,Lead initiatives to evaluate and introduce new tools, technologies, and frameworks that can enhance our data lifecycle and deliver competitive advantages.,Advocate for and contribute to the creation of maintainable, scalable, and future-proof data architectures, patterns, and standards for EDL and EDW.,Facilitate workshops and discussions to effectively convey data architecture principles and strategies across the enterprise.,Ensure continuous attention to data engineering excellence, good design, and governance, thereby driving agility and productivity.,Simplify data processes and systems, maximizing throughput, and removing bottlenecks to data engineering productivity while adhering to governance and compliance standards.,Provide mentorship and guidance to data engineers and architects, fostering a culture of learning and growth.,Stay abreast of industry trends and emerging technologies in data architecture, assessing their applicability to our goals and objectives.,Extensive experience in data architecture with a proven track record of innovation and productivity improvements in EDL/EDW environments.,Proficiency in data modeling, ETL/ELT processes, and technologies such as Hadoop, Spark, Snowflake, Databricks, or similar platforms.,Experience with DevOps practices, continuous integration, and continuous delivery (CI/CD) pipelines for data engineering.,Good understanding of Agile methodologies and principles, particularly those emphasizing collaboration, responsiveness to change, and customer focus.,Expert level critical thinking and ability to view the macro landscape for strategy and architecture.,Good understanding of development practices.

Bachelor's degree in Computer Science, Data Engineering, or a related field.,Extensive experience in data architecture with a proven track record of innovation and productivity improvements in EDL/EDW environments.,Proficiency in data modeling, ETL/ELT processes, and technologies such as Hadoop, Spark, Snowflake, Databricks, or similar platforms.,Experience with DevOps practices, continuous integration, and continuous delivery (CI/CD) pipelines for data engineering.,Good understanding of Agile methodologies and principles.,Expert level critical thinking.,Ability to step back and view the macro landscape for strategy and architecture.,Good understanding of development practices.,Understanding of data security principles and practices, including experience with data encryption, masking, and governance frameworks (Nice-to-have).,Experience with performance tuning, optimization, and monitoring of data pipelines and systems (Nice-to-have).,Familiarity with Generative AI and Large Language Models, and their application in data engineering (Nice-to-have).,Knowledge of cloud-based data platforms (e.g., AWS, Azure, GCP) and their native data services (Nice-to-have).,Enterprise architecture experience (Nice-to-have).,Solution architecture experience (Nice-to-have).

Bachelor's degree in Computer Science, Data Engineering, or a related field.