Senior Data Architect

GCI•Anchorage, AK

53d

About The Position

GCI's Senior Data Architect supports the Director of Data Architecture's mission to implement an enterprise data platform that enables data-driven decision-making in support of various business functions, aligning with organization vision and strategy. Responsible for analyzing, designing, and implementing architectural frameworks, data interfaces, tooling, and data quality technology to meet organizational needs for data management, accessibility, performance, and quality. ESSENTIAL DUTIES AND RESPONSIBILITIES AT ALL LEVELS: Technical Data Architecture & Implementation: Collaborate with data engineers, data scientists, and business analysts to ensure that data architecture effectively supports application and analytics needs. Design and develop an enterprise data lake, ensuring it supports a wide range of data types and formats while being scalable, reliable, secure, and efficient. Establish and enforce architectural frameworks and best practices, like medallion architecture, that guide the development of the data lake. Design and develop data models and pipelines that ensure data quality and are optimized to support self-serve analytics. Directly or with assistance of data engineering teams, integrate new data sources into the data lake, ensuring data is accessible and usable for analytics and reporting. Document essential technical architecture design and analysis efforts, including postmortem project documentation and metric collection. Mentor peers in the discipline of data architecture, providing guidance on technical skills and best practices. Data Governance & Data Quality Assurance: Implement data quality technologies and processes to monitor, assess, and provide insight to improve data accuracy and reliability. Collaborate with stakeholders and data governance leads to define data quality metric requirements for the data lake and ensure compliance with organizational standards. Help ensure that all data architecture practices adhere to organizational policies, industry regulations, and best practices. Implement tools and processes to track data lineage, ensuring transparency and traceability of data from source to consumption Data Architecture Strategy & Implementation: Assist in implementing a strategic vision for data architecture that aligns with GCI's business objectives and data management goals. Help define the architectural and logical requirements of data platforms. Engage with cross-functional teams, including data engineering, analytics, and business units, to ensure that data architecture aligns with business needs and enhances overall data management practices. On an ongoing basis evaluate the current technology and data environment to identify critical deficiencies and recommend solutions for improvement. Research & Innovation: Stay current with industry trends, emerging technologies, and best practices in data architecture and management, fostering continuous improvement and innovation within the data platform. Drive continuous improvement and innovation within the enterprise data platform in the areas of system performance, user experience and cost management. Ability to maintain professional skillset by advancing credentials, participating in training, continuing educational opportunities, and technical organizations. Ability to share technical skills, knowledge, and techniques with other technical staff. Ability to transfer knowledge to team members and customers Ability to accurately communicate information virtually (i.e., Teams), over the phone, and in-person in a clear and concise manner to a range of audiences. Ability to accurately read, write, and respond to business correspondence such as emails, chat messages, policies, procedures, reports. Ability to create clear and concise written communication (i.e., detailed documentation, diagramming, slide presentations) for a variety of audiences, including developers, business analysts, and business users. Ability to initiate and deliver technical information in presentation/training format in front of stakeholders. Proven ability to manage complex projects and strategic initiatives. Excellent analytical and problem-solving skills, with the ability to make data-driven decisions.

Requirements

High School diploma or equivalent.
Bachelor's degree in Computer Science, Systems Analysis, Engineering, or related field.
Minimum of ten (10) years of experience in software developmentor similar technical role.
Including a minimum of four (4) years of data architecture and design experience.
Demonstrated in-depth knowledge & experience with:
Master Data Management processes, policies, standards and tools.
Building data platforms to support operational and analytics reporting using an industry-standard open source or commercial BI/Analytics platforms.
Data design patterns, especially Lakehouse medallion architecture.
Proficiency in cloud platforms such as Azure and Databricks.
Declarative frameworks for building reliable, maintainable, and testable data pipelines e.g. Delta Live Tables (DLT), Databricks Asset Bundles.
Sql and NoSql data stores both cloud based and on-premise e.g. Azure Sql Database, CosmosDB, MySQL, Microsoft SQL Server, or Oracle.
Data processing, data engineering transformation patterns, and supporting technologies including a strong understanding of ETL, ELT patterns and (optionally) data streaming patterns.

Nice To Haves

Master's degree or PhD in relevant field.
Databricks Architecture/Data Engineering experience.
Telecommunications experience.
Relevant telecom industry or job specific certifications

Responsibilities

Collaborate with data engineers, data scientists, and business analysts to ensure that data architecture effectively supports application and analytics needs.
Design and develop an enterprise data lake, ensuring it supports a wide range of data types and formats while being scalable, reliable, secure, and efficient.
Establish and enforce architectural frameworks and best practices, like medallion architecture, that guide the development of the data lake.
Design and develop data models and pipelines that ensure data quality and are optimized to support self-serve analytics.
Directly or with assistance of data engineering teams, integrate new data sources into the data lake, ensuring data is accessible and usable for analytics and reporting.
Document essential technical architecture design and analysis efforts, including postmortem project documentation and metric collection.
Mentor peers in the discipline of data architecture, providing guidance on technical skills and best practices.
Implement data quality technologies and processes to monitor, assess, and provide insight to improve data accuracy and reliability.
Collaborate with stakeholders and data governance leads to define data quality metric requirements for the data lake and ensure compliance with organizational standards.
Help ensure that all data architecture practices adhere to organizational policies, industry regulations, and best practices.
Implement tools and processes to track data lineage, ensuring transparency and traceability of data from source to consumption
Assist in implementing a strategic vision for data architecture that aligns with GCI's business objectives and data management goals.
Help define the architectural and logical requirements of data platforms.
Engage with cross-functional teams, including data engineering, analytics, and business units, to ensure that data architecture aligns with business needs and enhances overall data management practices.
On an ongoing basis evaluate the current technology and data environment to identify critical deficiencies and recommend solutions for improvement.
Stay current with industry trends, emerging technologies, and best practices in data architecture and management, fostering continuous improvement and innovation within the data platform.
Drive continuous improvement and innovation within the enterprise data platform in the areas of system performance, user experience and cost management.
Ability to maintain professional skillset by advancing credentials, participating in training, continuing educational opportunities, and technical organizations.
Ability to share technical skills, knowledge, and techniques with other technical staff.
Ability to transfer knowledge to team members and customers
Ability to accurately communicate information virtually (i.e., Teams), over the phone, and in-person in a clear and concise manner to a range of audiences.
Ability to accurately read, write, and respond to business correspondence such as emails, chat messages, policies, procedures, reports.
Ability to create clear and concise written communication (i.e., detailed documentation, diagramming, slide presentations) for a variety of audiences, including developers, business analysts, and business users.
Ability to initiate and deliver technical information in presentation/training format in front of stakeholders.
Proven ability to manage complex projects and strategic initiatives.
Excellent analytical and problem-solving skills, with the ability to make data-driven decisions.
Collaborate with executive leadership and key stakeholders to understand business goals, translating them into specific data architecture requirements that support the company's five-year vision.
Conduct thorough analyses of industry trends, emerging technologies, and organizational needs to anticipate future data demands and inform architectural decisions and roadmaps.
Lead the design and development of enterprise grade relational and multi-dimensional data architectures for structured and un-unstructured data, including defining data models that optimize performance and accessibility for various business applications and analytical tools.
Apply understanding of data warehousing modeling techniques and their implementation on a modern data lakehouse.
Apply understanding of multi-hop architecture to incrementally and progressively improve the structure and quality of data as it flows through each layer of the architecture
Apply standard software development practices, including version control (e.g., DevOps, Git), infrastructure as code (IaC), continuous integration/continuous deployment (CI/CD), and automated testing to ensure high-quality and maintainable code.
Ability to lead and mentor a team of data architects and engineers, fostering a culture of collaboration, innovation, and continuous improvement.