About Lumen
Lumen connects the world. We are igniting business growth by connecting people, data and applications – quickly, securely, and effortlessly. Together, we are building a culture and company from the people up – committed to teamwork, trust and transparency. People power progress.
We’re looking for top-tier talent and offer the flexibility you need to thrive and deliver lasting impact. Join us as we digitally connect the world and shape the future.
The Role
The Senior Lead Analytics Engineer is a strategic and technical leader responsible for designing, building, and optimizing scalable data infrastructure and analytics solutions across Lumen’s marketing technology stack. This role sits at the intersection of data engineering and analytics, empowering marketing and sales teams with high-quality,
trusted data to drive insights, campaign performance, and strategic decisions.
A core focus of this role is relational data modeling—the ability to architect clean, scalable, and well-documented data models that reflect complex relationships across marketing platforms such as Salesforce Marketing Cloud, Marketo, and the Adobe Marketing Suite. You will work extensively within a Medallion architecture using tools like Microsoft Fabric, Power BI, and dbt, ensuring that data is structured in a way that supports intuitive reporting, analytics, and self-service exploration.

The Main Responsibilities

• Partner with the ops ingestion team to build and maintain scalable, efficient data pipelines using Microsoft Fabric and modern ELT tools.
• Design and implement relational data models that accurately represent business entities and their relationships, such as leads, campaigns, touchpoints, and conversions, across multiple marketing platforms.
• Normalize and structure data to reduce redundancy, improve query performance, and ensure consistency across reporting layers.
• Align data models with the Medallion architecture (Bronze, Silver, Gold layers) to support progressive refinement and analytics readiness.
• Integrate and transform data from Salesforce, Marketo, Adobe, and web analytics platforms into a unified, self-service reporting model that supports cross-channel insights and attribution.
• Ensure data accuracy, consistency, and availability across analytics platforms, with the ability to reverse engineer source applications for quality control and user acceptance testing.
• Develop intuitive dashboards and reports that support marketing strategy, campaign performance, and customer journey analytics.
• Collaborate with marketing strategists, campaign managers, dev-ops, and sales operations to understand data needs and deliver scalable, relationally sound solutions.
• Translate business questions into technical requirements and deliver insights that drive decision-making.
• Serve as a subject matter expert in analytics engineering, relational data modeling, and the modern data stack.
• Establish and promote best practices in data development, testing, documentation, and version control, with a focus on model scalability and maintainability.
• Evaluate and implement tools to improve data workflows, observability, and performance using the latest standards and ELT methodologies.
• Automate data validation, transformation, and deployment processes to ensure reliability and repeatability.

What We Look For in a Candidate

Required:

• Bachelor’s or master’s degree in computer science, Data Engineering, Marketing Analytics, or a related field.
• 5–8+ years of experience in analytics or data engineering, preferably in a marketing or commercial analytics context.
• Deep expertise in SQL and experience with ELT or similar data modeling tools.
• Proficiency in Microsoft Fabric, including Lakehouses, continuous integration and continuous delivery/deployment, notebooks, pipelines, and Power BI.
• Experience with Salesforce Marketing Cloud, Marketo, and Adobe Marketing Suite.
• Strong understanding of ELT/ETL processes, data warehousing, and data governance.
• Familiarity with Medallion architecture and cloud data platforms (e.g., Adobe CDP, Analytics SDK, Tag Management, and code versioning).
• Experience with Git-based version control and CI/CD for data workflows

Preferred:

• Hands-on experience designing and deploying relational data models, including star schemas, snowflake schemas, and normalized structures that support scalable analytics.
• Ability to model complex relationships between marketing entities such as campaigns, leads, accounts, and engagement metrics.
• Knowledge of cloud platforms (Azure, AWS, or GCP).
• Strong working knowledge of Salesforce backend development tools, including Workbench and Object Relational Manager.
• Familiarity with marketing attribution models and customer journey analytics.

Key Competencies

• Marketing Data Acumen: Understanding of KPIs, funnel metrics, attribution models, and campaign performance tracking.
• Technical Expertise: Deep knowledge of relational data modeling, transformation, and orchestration tools.
• Analytical Thinking: Proactive approach to identifying and resolving data issues.
• Communication: Ability to translate business needs into technical solutions.
• Initiative: Self-driven and comfortable working independently in a fast-paced, matrixed environment.
• Attention to Detail: High standards for data quality, documentation, and testing.

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:
$103,711 - $138,281 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, and WY.
$108,896 - $145,195 in these states: CO, HI, MI, MN, NC, NH, NV, OR, and RI.
$114,082 - $152,109 in these states: AK, CA, CT, DC, DE, IL, MA, MD, NJ, NY, TX, VA, and 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.
What to Expect Next

LI-KM2

Requisition #: 339211
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.
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.
Application Deadline
08/09/202

• Partner with the ops ingestion team to build and maintain scalable, efficient data pipelines using Microsoft Fabric and modern ELT tools.
• Design and implement relational data models that accurately represent business entities and their relationships, such as leads, campaigns, touchpoints, and conversions, across multiple marketing platforms.
• Normalize and structure data to reduce redundancy, improve query performance, and ensure consistency across reporting layers.
• Align data models with the Medallion architecture (Bronze, Silver, Gold layers) to support progressive refinement and analytics readiness.
• Integrate and transform data from Salesforce, Marketo, Adobe, and web analytics platforms into a unified, self-service reporting model that supports cross-channel insights and attribution.
• Ensure data accuracy, consistency, and availability across analytics platforms, with the ability to reverse engineer source applications for quality control and user acceptance testing.
• Develop intuitive dashboards and reports that support marketing strategy, campaign performance, and customer journey analytics.
• Collaborate with marketing strategists, campaign managers, dev-ops, and sales operations to understand data needs and deliver scalable, relationally sound solutions.
• Translate business questions into technical requirements and deliver insights that drive decision-making.
• Serve as a subject matter expert in analytics engineering, relational data modeling, and the modern data stack.
• Establish and promote best practices in data development, testing, documentation, and version control, with a focus on model scalability and maintainability.
• Evaluate and implement tools to improve data workflows, observability, and performance using the latest standards and ELT methodologies.
• Automate data validation, transformation, and deployment processes to ensure reliability and repeatability