Lumen is the trusted network for AI. We’re transforming how businesses connect, secure, and scale in an AI-driven world. By connecting people, data, and applications quickly, securely, and effortlessly, we help organizations move faster and unlock what’s next. At Lumen, people power progress. Our culture is built on teamwork, trust, and transparency, giving you the flexibility, support, and opportunity to make a lasting impact. We’re looking for top-tier talent ready to take on the challenge. Join us in building the future. The Role The Data Governance Officer is responsible for establishing and operating Lumen’s enterprise data governance foundation. This role will define clear roles, accountability, standards, and decision-making mechanisms for data across the enterprise. Reporting to the Chief Data Officer, this role operationalizes centralized governance with federated ownership, ensures stewardship for all master data domains, and defines enterprise data architecture direction across platforms and technologies. The Data Governance Officer runs the Enterprise Data Council (EDC) as the authoritative body governing data ownership, standards, architecture direction, and risk. This role is accountable for improving the trust, transparency, and consistency of Lumen’s data assets by embedding governance into how the enterprise operates — across Product, Engineering, Network, Security, and functional organizations. The ideal candidate is a disciplined operator who can translate governance principles into durable enterprise mechanisms and ensure governance serves the entire enterprise, not individual teams. Location This is a remote position open to candidates located anywhere in the U.S. The Main Responsibilities - Establish and operationalize formal enterprise data governance, including defined roles, decision rights, and accountability. - Run the Enterprise Data Council (EDC), providing authoritative, enterprise level governance over data ownership, standards, architecture direction, and risk. - Define and enforce a federated data stewardship model, with data ownership and stewardship residing in the business and centralized standards enabled by the CDO organization. - Establish and manage master data domains, critical data elements, and ownership accountability across the enterprise. - Publish and maintain enterprise data quality and governance scorecards to improve trust and transparency of data assets. - Define and enforce enterprise data standards, including business glossary, modeling practices, and architectural consistency. - Along with Tech and Engineering, define and co-own enterprise data architecture strategy across platforms, technologies, and functional organizations, reducing ambiguity and fragmentation. - Manage and mature data governance tooling and processes, including catalog, lineage, and data quality capabilities. - Ensure governance supports AI governance requirements, including legally responsible, compliant, and defensible AI use, data readiness, control, and trust. - Partner with Product, Engineering, Network, and Security to ensure governance capabilities are STEP aligned and enterprise serving, enabling consistent outcomes across the company. What We Look For in a Candidate - 15+ years of experience in data, analytics, technology, or architecture leadership, with experience establishing enterprise data governance. - Proven track record of standing up formal data governance foundations in complex, federated organizations. - Deep expertise in data ownership models, stewardship, master data, data standards, and enterprise data architecture. - Experience operating centralized governance with federated ownership, balancing control with business accountability. - Strong understanding of data quality, metadata, lineage, and governance tooling as operational enablers, not standalone solutions. - Ability to lead and influence through enterprise councils and governance forums, including executive level stakeholders. - A clear, structured communicator capable of establishing standards, resolving ambiguity, and driving alignment across platforms and functions. - Experience supporting enterprise AI governance, including data readiness, control, trust, and compliance. - Bachelor’s degree required; Master’s degree preferred. Compensation This information reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual pay is based on skills, experience and other relevant factors. Location Based Pay Ranges $174,876 - $233,168 in these states: AL AR AZ FL GA IA ID IN KS KY LA ME MO MS MT ND NE NM OH OK PA SC SD TN UT VT WI WV WY $183,621 - $244,827 in these states: CO HI MI MN NC NH NV OR RI $192,364 - $256,486 in these states: AK CA CT DC DE IL MA MD NJ NY TX VA WA Lumen offers a comprehensive package featuring a broad range of Health, Life, Voluntary Lifestyle benefits and other perks that enhance your physical, mental, emotional and financial wellbeing. We're able to answer any additional questions you may have about our bonus structure (short-term incentives, long-term incentives and/or sales compensation) as you move through the selection process. Learn more about Lumen's:BenefitsBonus Structure Requisition #: 341794 Background Screening If you are selected for a position, there will be a background screen, which may include checks for criminal records and/or motor vehicle reports and/or drug screening, depending on the position requirements. For more information on these checks, please refer to the Post Offer section of our FAQ page. Job-related concerns identified during the background screening may disqualify you from the new position or your current role. Background results will be evaluated on a case-by-case basis. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Equal Employment Opportunities We are committed to providing equal employment opportunities to all persons regardless of race, color, ancestry, citizenship, national origin, religion, veteran status, disability, genetic characteristic or information, age, gender, sexual orientation, gender identity, gender expression, marital status, family status, pregnancy, or other legally protected status (collectively, “protected statuses”). We do not tolerate unlawful discrimination in any employment decisions, including recruiting, hiring, compensation, promotion, benefits, discipline, termination, job assignments or training. Privacy Notice Lumen is committed to protecting the privacy and security of personal information collected during the recruitment and hiring process. Our Privacy Notice explains how we collect, use, disclose, and protect applicant information, as well as how individuals may request access to or deletion of their personal data. To review Lumen’s Privacy Notice, please visit: https://jobs.lumen.com/global/en/privacy-notice Disclaimer The job responsibilities described above indicate the general nature and level of work performed by employees within this classification. It is not intended to include a comprehensive inventory of all duties and responsibilities for this job. Job duties and responsibilities are subject to change based on evolving business needs and conditions. In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information. Please be advised that Lumen does not require any form of payment from job applicants during the recruitment process. All legitimate job openings will be posted on our official website or communicated through official company email addresses. If you encounter any job offers that request payment in exchange for employment at Lumen, they are not for employment with us, but may relate to another company with a similar name.

• Lead the implementation of Snowflake solutions • Build scalable and maintainable ETL/ELT pipelines • Design and implement robust data integration pipelines • Lead efforts in migrating legacy data systems to a modern cloud-based stack • Own the end-to-end data lifecycle • Collaborate with product, data science, and analytics teams • Create and manage reports and dashboards using Power BI • Drive performance tuning, cost optimization, and security enforcement within the Snowflake platform • Utilize SQL and Python for ETL, data manipulation, analysis, and process automation

Description The Microsoft Fabric Data Engineer is responsible for designing, building, and maintaining scalable, secure, and high-performance data pipelines and data models within Microsoft Fabric. This role focuses on ingesting data from multiple enterprise source systems into OneLake, transforming data across Bronze, Silver, and Gold layers, and enabling trusted, analytics-ready datasets for reporting, dashboards, and advanced analytics. The ideal candidate has hands-on experience with Microsoft Fabric, Lakehouse architecture, and modern ELT patterns, and works closely with Power BI developers and business stakeholders to deliver reliable and governed data solutions. Requirements Data Engineering & Pipelines - Design, develop, and maintain end to end data pipelines in Microsoft Fabric using Pipelines, Dataflows Gen2, and Notebooks - Ingest structured and semi structured data from SQL databases, APIs, SFTP, CSV, SaaS platforms, and file based sources into OneLake - Implement incremental and full load ingestion strategies with error handling, logging, and monitoring Lakehouse & Data Modeling - Build and manage Lakehouse architectures following Bronze, Silver, and Gold data patterns - Perform data cleansing, standardization, and transformation to produce analytics ready fact and dimension tables - Optimize data models to support Direct Lake and Power BI semantic models Performance, Reliability & Optimization - Optimize pipeline execution, storage layout, and query performance across Fabric workloads - Monitor capacity usage and proactively identify performance bottlenecks - Troubleshoot and resolve data quality, pipeline, and refresh failures Security, Governance & Compliance - Implement data security controls using Microsoft Entra ID, workspace roles, and access policies - Support data governance, lineage, and cataloging through Microsoft Purview - Follow enterprise standards for data retention, privacy, and compliance (HIPAA/HITRUST where applicable) Collaboration & Delivery - Partner with Power BI Developers to ensure datasets are optimized for reporting and analytics - Work with business and analytics teams to understand data requirements and translate them into technical solutions - Support UAT, production deployments, and ongoing enhancements DevOps & Best Practices - Participate in CI/CD processes using Azure DevOps or equivalent tooling for data assets - Maintain technical documentation, data dictionaries, and pipeline design artifacts - Contribute to data engineering standards, frameworks, and reusable patterns Qualifications: Education: - Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience) Qualifications: - Hands-on experience with Microsoft Fabric (Lakehouse, Pipelines, Notebooks, OneLake) - Strong proficiency in SQL and data transformation logic - Experience with modern data architecture concepts (ELT, Lakehouse, dimensional modeling) - Experience with Azure data services (Azure Data Factory, Synapse, SQL, Storage) - Familiarity with Power BI and Direct Lake integration patterns - Experience with CI/CD for data platforms - Healthcare or regulated-industry data experience - Microsoft Fabric, Azure Data Engineer, or related certifications Skills: - Strong analytical and problem-solving skills - High attention to data accuracy, quality, and reliability - Ability to work cross-functionally with technical and non-technical stakeholders - Strong documentation and communication skills - Ability to manage multiple data initiatives in parallel

• Design, implement, and maintain data pipelines to access data sources • Develop processes for staging data, performing ETL/ELT operations and moving data to the appropriate data flows. • Collaborate with data engineers, data analysts, and business stakeholders to understand data requirements and ensure alignment to Use Case • Perform design engineering to ensure the data pipeline meets the Product’s Data Contract for currency, throughput, and performance.