Senior Manager, Data Streaming Engineering – Guest Profile

At Disney Experiences Technology, our team creates world-class immersive digital experiences for the Company’s premier vacation brands including Disney’s Parks & Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club. The Disney Experiences Technology team is responsible for the end-to-end digital and physical Guest experience for all technology & digital-led initiatives across the Attractions & Entertainment, Food & Beverage, Resorts & Transportation, and Merchandise lines of business as well as other initiatives including the MyDisneyExperience app and Hey, Disney!

Do you love to power magical experiences at scale with data? Join us! We are seeking a senior engineering leader to own the strategy, architecture, and delivery of our real-time Guest Profile, enabling real-time identity, personalization, and insights across Disney Experiences. You will lead a high-performing team of data streaming engineers to design, build, and operate event-driven pipelines and services that ensure Guest data is fresh, accurate, secure, and privacy-first. Your work will directly enable teams across Disney to create seamless, personalized experiences for millions of Guests.

You will sit in Data Products & Platform within the Technology & Digital organization for Disney Experiences and partner closely with business strategy, product, privacy, identity, technology, and engineering leaders across segments and company.

What you’ll do

• Own the end-to-end strategy and roadmap for real-time Guest Profile data capabilities, including identity events, consent signals, profile enrichment, and downstream activation integrations.
• Lead the design and implementation of a modern, event-driven streaming architecture (ingestion, processing, enrichment, storage, activation) with strong SLAs/SLOs for latency, freshness, reliability, and data quality.
• Define and enforce data contracts, schemas, and governance for Guest-related events and profile attributes; establish best practices for schema evolution, versioning, replay, and backfills.
• Build and operate stateful streaming pipelines for identity resolution (deterministic and probabilistic), account/device/household stitching, and profile graph updates.
• Implement privacy-by-design into every streaming path: consent and preference enforcement in-stream, data minimization, purpose limitation, and secure handling of sensitive and PII data.
• Create real-time data products and services (e.g., profile change feeds, consent event topics, feature streams) that power personalization, marketing activation, service recovery, and analytics.
• Establish operational excellence: production readiness standards, incident response, on-call, capacity planning, and robust observability for streaming workloads.
• Build, mentor, and grow a diverse, world-class engineering team; set clear goals/OKRs, foster engineering excellence, and develop leaders within the organization.
• Communicate strategy, trade-offs, and technical direction to executive and non-technical audiences; influence across a matrixed environment to drive adoption of streaming-first patterns.
• Evaluate and introduce emerging capabilities (e.g., Snowpipe Streaming, dynamic tables, stream-native quality checks, open lineage) to continuously improve speed, safety, and cost efficiency.
• Stay current on consumer privacy regulations and platform changes; translate shifts in the privacy landscape into proactive adjustments to the Guest data streaming strategy.

Required qualifications and skills

• 10+ years of experience in data engineering or software engineering, including a minimum of 5+ years leading teams that build and operate real-time/streaming data systems in production.
• Deep expertise in event streaming technologies and patterns, including Kafka/Confluent (or Pulsar/Kinesis/Pub/Sub), Kafka Connect, Schema Registry (Avro/Protobuf/JSON), and CDC frameworks (e.g., Debezium).
• Stream processing engines such as Apache Flink, Spark Structured Streaming, or Beam/Dataflow; strong understanding of stateful processing, checkpointing, and idempotency.
• Advanced knowledge in data architecture and lakehouse patterns, including formats like Parquet/Iceberg/Delta and stream-to-lake/warehouse integrations.
• Experience delivering automated, highly available ETL/ELT pipelines at scale with robust CI/CD, infrastructure as code, and container orchestration (Kubernetes).
• Experience across data warehouse platforms such as Snowflake and BigQuery, with expert-level knowledge in Snowflake and streaming integrations (e.g., Snowpipe Streaming, dynamic tables).
• Proficiency with orchestration, testing, and data quality tools for streaming and batch (e.g., Airflow, dbt for ELT where applicable, Anomalo, Great Expectations, OpenLineage).
• Strong observability and reliability practices: metrics, tracing, logging, and alerting for data systems (e.g., Datadog, Prometheus, OpenTelemetry); SLO/SLI design and incident management.
• Hands-on programming experience in one or more of Java/Scala/Kotlin/Python for data pipeline and platform development.
• Demonstrated expertise in data security and privacy: consent management, PII handling, tokenization, access controls, and compliance with GDPR/CCPA and related regulations.
• Outstanding communication, storytelling, and stakeholder management skills; proven ability to influence across a matrixed organization.
• Inclusive, collaborative leadership that develops geographically distributed, highly technical teams and fosters a culture of excellence, accountability, and continuous improvement.
• Ability to operate with urgency and discipline in a fast-paced, evolving environment.

Required education

• Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field; or equivalent work experience.

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