About the Role

At Uber, we ignite opportunity by setting the world in motion. The Data Solutions team within Performance Marketing is looking for an inventive, passionate and technical Marketing Technology Manager II to help support and grow our business.

In this role, you'll blend technical execution, marketing understanding, and operational excellence. You'll own projects end-to-end and support larger initiatives, building and improving data pipelines, automating workflows, strengthening observability, and enabling marketers with scalable systems. You'll partner closely with Ad Tech, Data Science, Product, and Engineering to improve the reliability and impact of Uber's performance marketing ecosystem.

This is a hands-on role for someone equally comfortable writing SQL, managing technical configurations, debugging data feeds, collaborating with engineering, and guiding marketers toward data-driven solutions. You'll help define how data flows across platforms, ensuring campaigns are powered by accurate, timely, and actionable data. You'll also be a thought leader to our stakeholders, acting as a subject matter expert of our data ecosystem and nuances, bridging technical knowledge gaps, and driving Single-Source-of-Truth reporting on data issues.

What You'll Do:

1. Lead data solutions projects end-to-end: Scope, plan, execute, and deliver measurable outcomes, while supporting large-scale initiatives with senior partners.2. Architect and improve data pipelines: Design, validate, manage, and enhance ingestion and sharing flows across internal and external systems (APIs, warehouses, tracking platforms).3. Operationalize reliability and observability: Define standards for monitoring, alerting, documentation, and service ownership; improve uptime and error transparency across pipelines.4. Automate and scale operations: Build tooling (scripts, dashboards, utilities) to reduce manual work, standardize validation, and increase visibility across stakeholders.5. Drive incident-style investigations and resolution: Lead investigations into data discrepancies or performance anomalies, deliver crisp root cause narratives, and drive durable fixes with partner teams.6. Influence cross-functional stakeholders: Informally lead across XFN groups (Marketing, Product, Ad Tech, Engineering, Data Science), align on priorities, and communicate progress, risks, and decisions.7. Communicate with clarity and leverage narrative: Autonomously craft compelling narratives and decks for project updates, decision-making, and leadership visibility (including some L+2 exposure).8. Governance and standards: Help maintain taxonomy, event mappings, and best practices that ensure data quality and compliance, and onboard quickly to new domains as needs evolve.

Basic Qualifications:

1. Bachelor's degree in a technical/quantitative field (Computer Science, Engineering, Mathematics), or Marketing degree with strong technical experience.
2. Strong working knowledge of SQL, APIs, and data pipeline tools (ETL, Airflow, dbt, or equivalent).
3. Experience with marketing data (e.g., pixel tracking, event sharing, attribution, or ads platform APIs).
4. Demonstrated ability to debug data issues, communicate root causes, and deliver data-driven recommendations.
5. Track record of designing and documenting systems that increase operational resilience and visibility.
6. Ability to thrive in ambiguity, context-switch across business and technical stakeholders, and deliver high-quality, timely results.
7. Strong stakeholder management skills: ability to build alignment, navigate ambiguity, and coordinate work across cross-functional partners to drive outcomes.
8. Comfortable challenging the status quo, applying critical thinking, setting high standards to think ambitiously and creatively to build and validate various hypotheses

Preferred Qualifications:

1. 4+ years of experience in data engineering, marketing technology, analytics, or ad operations.
2. Experience working directly with product, engineering and data science teams to build in-house or API-based solutions.
3. Familiarity with cloud data environments (e.g., GCP, Big Query) and marketing APIs (e.g., Meta, Google Ads, Tik Tok).
4. Understanding of A/B testing frameworks, campaign measurement, and marketing attribution models.
5. Comfort with lightweight coding (Python or equivalent scripting languages).
6. Experience establishing operational standards (monitoring, documentation, incident response patterns) for data products or marketing data pipelines.

• For San Francisco, CA-based roles: The base salary range for this role is USD**$142,000 per year**
• USD**$158,000 per year**.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.