Data Engineering Manager

NBCUniversal • Miami, FL

1d

About The Position

The Data Engineering Manager will be a hands-on data engineering role supporting Universal+, Hayu, and the wider NBCUniversal International Networks & Direct-to-Consumer business, with a particular focus on local delivery and stakeholder needs in Florida and Latin America. Reporting to the Senior Director, Data Platform, this role will build and maintain reliable data solutions across Snowflake, cloud data platforms, ETL/ELT pipelines, integrations, orchestration, and reporting environments. The role will also coordinate local data initiatives, manage dependencies and delivery plans, and act as a key bridge between business stakeholders, product teams, analytics teams, vendors, and the wider International Data Platform team.

Requirements

• Experience designing, building, and supporting data engineering solutions in a commercial environment, ideally across streaming, media, broadcast, or subscription businesses.
• Strong hands-on data engineering experience across ETL/ELT pipelines, SQL transformations, APIs, file-based integrations, orchestration, automation, and production support.
• Strong SQL and Snowflake experience, including data modelling, performance tuning, access controls, troubleshooting, and practical optimisation of warehouse usage.
• Project coordination experience, including planning, dependency management and stakeholder status reporting.
• Python or equivalent programming experience, with the ability to build maintainable, observable, and reusable engineering components.
• Experience working with cloud services, preferably AWS, including data lake storage, serverless compute, orchestration, identity and access management, monitoring, and infrastructure automation.
• Good understanding of data governance, privacy, security, access control, data quality, lineage, and operational support practices for enterprise data platforms.
• Must be 18 years or older
• Must be willing to submit to a background investigation
• Must have unrestricted work authorization to work in the United States
• Must be covered by Solutions, NBCU’s Alternative Dispute Resolution Program

Nice To Haves

• Hands-on engineer who is comfortable owning practical delivery while coordinating priorities across multiple stakeholders.
• Comfortable acting as a local point of contact for data platform work, balancing regional business needs with shared global team standards.
• Pragmatic, organised, and quality-focused, with strong judgement on when to move quickly, when to simplify, and when to invest in long-term platform resilience.
• Able to communicate technical topics clearly, manage expectations, escalate risks early, and build trust across engineering, product, analytics, and business teams.

Responsibilities

• Hands-on Data Engineering: Design, build, test, deploy, and support reliable data pipelines, data models, integrations, and reporting datasets across Snowflake and related cloud data platform services.
• Local Data Delivery: Support local business and product priorities by translating stakeholder requirements into practical, maintainable data engineering solutions.
• Snowflake & Data Platform Support: Develop and maintain Snowflake objects, SQL transformations, data models, secure access patterns, performance tuning, and cost-conscious platform usage.
• Integrations & Automation: Build and support integrations between the data platform and internal or third-party systems, including analytics, CRM, marketing technology, partner platforms, finance systems, content systems, and operational tooling.
• Project Coordination: Coordinate project plans, priorities, dependencies and stakeholder updates for local and regional data initiatives.
• Stakeholder Management: Act as a local point of contact for product, analytics, finance, marketing, operations, commercial, content, and technology stakeholders, ensuring requirements, priorities, risks, and delivery status are clearly understood.
• Data Quality, Governance & Support: Monitor and improve data quality, pipeline reliability, documentation, access controls, privacy, security, lineage, and operational support processes.
• Team Collaboration: Work closely with data engineers, analysts, product owners, engineering teams, vendors, and enterprise technology partners to deliver well-documented and maintainable solutions.
• Continuous Improvement: Identify opportunities to simplify processes, automate manual workflows, improve data quality, reduce operational effort, and unlock new datasets that support reporting, insight, activation, AI, and governance use cases.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed