Director, Product Data Architecture

amcn; New York (NY); On-site; USD 170,000 - 230,000; Full time

Job summary

AMC Global Media is seeking a Director, Product Data Architecture to join our Streaming Product & Operations team in New York, NY. You will own end-to-end data architecture for streaming product data, including lakehouse evolution, data contracts, and governance across identity, content, viewership, and monetization domains.

Collaborate with product, engineering, analytics, and vendor partners to design scalable data platforms, ensure data quality, privacy, and cost efficiency, and enable BI,

Qualifications

• 8+ years designing and operating modern data platforms at scale.
• Has designed and operated lakehouse or equivalent architectures.
• Depth in dimensional and semantic modeling of product and behavioral data.
• Fluency with event-driven instrumentation, schema governance, and data contracts.
• Technical owner of platform and vendor recommendations, with executive-facing communication.
• Embedded partner to PM and engineering, shaping instrumentation and definitions.
• Hands-on: writes and reviews code and designs.
• Excellent communication and executive presence for business terms.
• Models subscription and billing data across multiple purchase channels.

Responsibilities

• End-to-end data architecture for streaming product data, including lakehouse assessment and future path.
• Define canonical metrics and semantic layer with governance and owners.
• Instrumentation and collection: event taxonomy and schema design for web, mobile, and TV.
• Tooling and vendor recommendations for CDP and analytics stack; present for approvals.
• Design data domains: subscription, identity, content, viewership, ads, lifecycle data.
• Integrate partner and third-party data with reconciliation to our data.
• Provide analytics enablement for BI, experimentation, and ML use cases.
• Ensure data quality, lineage, SLAs, and incident handling.
• Privacy, retention, and regional compliance embedded in architecture.
• Cost and efficiency considerations for compute and storage.
• Set engineering standards and mentor engineers on technical craft.

Skills

Data architecture

Lakehouse design

Dimensional modeling

Event-driven data

Vendor management

Cross-functional collaboration

Coding experience

Communication to leadership

Tools

Databricks

Snowflake

Iceberg/Delta

Job description

Job Description

AMC Global Media is home to many of the greatest stories and characters in TV and film and the premier destination for passionate and engaged fan communities around the world.

We create and curate celebrated series and films across distinct brands and make them available to audiences everywhere. Our portfolio includes targeted streaming services AMC+, Acorn TV, Shudder, Sundance Now, ALLBLK and HIDIVE; cable networks AMC, BBC AMERICA, Independent Film Company, Sundance TV and We TV; and film distribution labels Independent Film Company and RLJE Films. The company also operates AMC Studios, our in-house studio, production, and distribution operation behind acclaimed and fan-favorite originals including The Walking Dead Universe and the Anne Rice Immortal Universe, and AMC Networks International, our international programming business.

We are currently seeking a Director, Product Data Architecture to join our Streaming Product & Operations team in our New York, NY location.

JOB RESPONSIBILITIES:

• Product data architecture. The end-to-end design for how streaming product data is produced, modeled, stored, and served, including assessment of the current lakehouse implementation and a point of view on the path forward from where we are today, whether that is evolution or replacement.
• Contracts and definitions. A canonical metric and semantic layer for product data, with producer-side enforcement and a governance model with named owners for every definition.
• Instrumentation and collection. Event taxonomy and schema design across web, mobile, and connected TV clients, and the standards product engineering and partner teams build against.
• Tooling and vendor recommendations. Owns the technical evaluation and recommendation on the product data and analytics stack, including our CDP and analytics footprint (mParticle, Mixpanel, and adjacent tooling), and carries those recommendations to the leadership and procurement approvals that larger commitments require.
• Product data domains. Subscription and identity, content and catalog, viewership and engagement, advertising and monetization, and promotional and lifecycle data. Subscription is the hardest of these: purchase, entitlement, and lifecycle data arrives from direct billing (Stripe), in-app purchase (Apple, Google Play, Amazon, Roku), and partner-billed channels, each with its own event semantics, identifiers, and treatment of trials, proration, refunds, and cancellations. Designing the aggregation and reconciliation model that makes subscriber state trustworthy across all of them is core to the role.
• Partner and third-party data. Integration architecture for distribution and platform partners, ad and billing systems, and outbound feeds to downstream consumers, including reconciliation of platform-reported data against our own.
• Analytics and activation enablement. Models and interfaces that let product, marketing, analytics, and data science teams serve BI, experimentation, personalization, and machine learning use cases without each consumer rebuilding logic.
• Reliability and observability. Data quality monitoring, lineage, SLAs on critical product datasets, and the incident model when they are missed.
• Privacy and compliance. Consent propagation, data retention, PII handling, and regional requirements designed into the architecture rather than bolted on.
• Cost and efficiency. Compute and storage economics of the product data platform, and the tradeoffs behind them.
• Engineering standards. Modeling conventions, review patterns, and the technical bar for product data work, including mentorship of engineers on technical craft.

QUALIFICATIONS (Required & Preferred)

• 8+ years of experience in designing and operating modern data platforms at scale.
• Has designed and operated modern data platforms at scale, including lakehouse or equivalent architectures (Databricks, Snowflake, Iceberg, Delta, or similar), through at least one full lifecycle from design to production to iteration
• Depth in dimensional and semantic modeling of product and behavioral data, with a clear point of view on metric layers and data contracts
• Fluency with event-driven and behavioral data: instrumentation design, schema governance, and the failure modes of client-side event collection
• Track record as the technical owner of platform and vendor recommendations, including building the case and defending it to executive stakeholders
• Has worked as an embedded partner to product management and product engineering, shaping instrumentation and definitions as part of the product development process rather than after it
• Hands‑on. Still writes and reviews code and designs
• Excellent communication skills and executive presence, with the ability to translate architectural tradeoffs into business terms for senior leadership
• Leads through influence across engineering, product, analytics, and vendor partners
• Has modeled subscription and billing data across multiple purchase channels, including direct bi