Senior Director of Data Engineering and Transformation

Lumen Technologies•,

8d•$174,876 - $256,486•Remote

About The Position

Lumen is the trusted network for the AI‑powered world, connecting people, data, and applications through our expansive fiber network and connected ecosystem. We enable secure, high‑performance connectivity across cloud, edge, and AI workloads for enterprises, governments, and communities. At Lumen, you’ll work on infrastructure customers rely on today and build for what’s next, where performance, security, and resilience matter. This is a high accountability environment where bold ideas drive real innovation for our customers, partners, and industry. The work is challenging, expectations are clear, and trust is built into how we operate. If you’re ready to take ownership, deliver meaningful impact, and help shape the future of AI‑ready connectivity, join us today. The Role We are seeking an experienced, hands-on Senior Director of Data Engineering & Transformation to lead the modernization, execution, and optimization of enterprise data platforms, architectures, and engineering capabilities across Lumen. This leader will drive scalable data products, modern pipelines, integration frameworks, and AI-ready data structures that enable analytics, artificial intelligence, business decision-making, and increased automation. In this role, the Senior Director will shape the company’s data landscape by modernizing platforms, improving engineering practices, and accelerating the organization’s ability to use data as a strategic asset. The position also focuses on making Lumen data more accessible and consumable for business users, enterprise applications, and AI agents to improve productivity and unlock greater business value, while ensuring data governance requirements such as quality, security, lineage, access controls, metadata, and compliance are embedded into technical solutions and architecture practices.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related field. Advanced degree preferred.
15+ years of experience in data engineering, data architecture, enterprise data platforms, data integration, data transformation, or related technical disciplines.
Strong experience designing and implementing large-scale data architectures, modern data platforms, enterprise data pipelines, and data engineering solutions.
Deep knowledge of ETL/ELT pipelines, data ingestion, data transformation, data modeling, data warehousing, lakehouse architectures, cloud data platforms, and distributed data systems.
Experience structuring data for analytics, reporting, AI, machine learning, business intelligence, intelligent applications, and automation use cases, including applied AI for data and AI-agent consumption patterns.
Experience structuring data for analytics, reporting, AI, machine learning, and business intelligence use cases.
Strong understanding of data quality, security, metadata, lineage, access management, and governance requirements as part of technical delivery.
Proven ability to lead technical teams and manage complex data engineering, architecture, and transformation programs.
Strong communication skills with the ability to translate technical concepts into executive-level presentations, transformation roadmaps, and business-facing recommendations.
Experience evaluating, selecting, and implementing data technologies, platforms, and engineering frameworks.

Nice To Haves

Experience with data analytics, business intelligence, applied AI for data, AI agents, automation enablement, and machine learning enablement platforms.
Experience with data analytics, business intelligence, AI, and machine learning enablement platforms.
Familiarity with cloud-based data platforms and services such as Azure, AWS, Google Cloud, Snowflake, Databricks, Microsoft Fabric, or similar technologies.
Experience with data mesh, lakehouse architecture, domain-oriented data products, metadata management, feature stores, vector databases, or AI-ready data platform design.
Experience with DevOps, DataOps, CI/CD, orchestration, monitoring, testing automation, and production support for data platforms and pipelines.
Certification in cloud architecture, data engineering, data architecture, or data management preferred.

Responsibilities

Transform enterprise data infrastructure by modernizing data platforms, architectures, pipelines, and engineering practices.
Make data more available and consumable for business users, enterprise applications, analytics platforms, and artificial intelligence.
Design scalable enterprise data architectures that support analytics, AI, automation, reporting, and operational use cases.
Lead data pipeline development and optimization, including ETL/ELT, ingestion, transformation, orchestration, monitoring, testing, and production support.
Drive data platform modernization across cloud, lakehouse, integration, storage, analytics, and AI-enablement capabilities.
Deliver reusable data products and solutions, including APIs, semantic layers, governed access patterns, analytical datasets, and AI-ready data structures.
Enable AI-ready data architecture for machine learning, intelligent applications, AI agents, advanced analytics, and automation workflows.
Lead complex transformation initiatives from strategy through execution, including roadmaps, milestones, dependencies, risks, and measurable business outcomes.
Embed governance into technical delivery, including data quality, security, lineage, metadata, access controls, compliance, and responsible data use.
Lead and mentor technical teams across data architecture, data engineering, platform engineering, and technical delivery while fostering excellence, accountability, and innovation.