Director, Product Management - Data Platform

Asurion•San Mateo, CA

3d•Hybrid

About The Position

Asurion — the world’s leading connected device protection company, serving 300M+ customers — is looking for a hands-on Director of PM to own the strategy and roadmap for our Data Platform. You understand both sides: how data is produced and how it’s consumed. You know how to build the foundational infrastructure — data catalog, lineage, ingestion pipelines, access governance, and a self-service analytics layer — that turns raw data into a trusted, scalable asset. This is a high-visibility role with broad scope and the mandate to shape how the entire organization works with data.

Requirements

10+ years in product management, with a significant focus on data platform, infrastructure, or analytics products.
Fluency with the modern data stack: Databricks (Delta Lake, Unity Catalog, MLflow), Snowflake, Amazon EMR/Spark, and cloud-native data services on AWS or GCP.
Experience building or evolving core platform capabilities: data catalog, metadata management, column-level lineage, pipeline orchestration (Airflow, dbt, or similar), RBAC, and data quality frameworks.
Understands the producer/consumer dynamic — knows that a great platform is as much about how data gets in as how it gets used.
Proven cross-functional leadership; strong communicator from the board room to the engineering standup.
Customer-obsessed with a strong bias for outcomes over output.

Nice To Haves

Experience standing up a data mesh or domain-oriented data ownership model.
Familiarity with ML/AI workflows and feature stores that consume platform data.
Background partnering with security and privacy teams on governance at scale.

Responsibilities

Own the Data Platform roadmap: from ingestion and pipeline orchestration to data catalog, lineage tracking, access governance, and the self-service analytics layer.
Define how teams onboard data to the platform — establishing contracts, SLAs, quality checks, and documentation standards that make data trustworthy at the source.
Drive the self-service experience — so analysts and data scientists can discover, access, and use data in tools like Databricks notebooks or Snowflake without filing tickets.
Partner with engineering on architecture decisions: when to use streaming vs. batch, how to structure the lakehouse, what belongs in the warehouse vs. the lake.
Align data engineering, analytics, data science, security, and business stakeholders around a shared platform vision.
Hire, develop, and lead a high-performing team of data-fluent PMs.