<p>We are looking for a Data Engineer to join the client’s User Platforms organization. This role will be responsible for building and scaling the data foundation that powers experimentation, causal analysis, product optimization, and decision-making across Disney+, Hulu, ESPN+, and other streaming products.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><p>·      Design, develop, and maintain scalable experimentation data platforms supporting A/B testing, geo experiments, feature launches, and product analytics.</p><p>·      Build and optimize batch and streaming data pipelines that ingest, transform, validate, and serve large-scale user behavior, product, and engagement datasets.</p><p>·      Create reusable experimentation frameworks, datasets, and tooling that enable teams to efficiently define experiments, measure outcomes, and analyze results.</p><p>·      Design dimensional models, analytical data products, and feature-ready datasets optimized for analytics, experimentation, and machine learning use cases.</p><p>·      Implement automated data quality validation, monitoring, lineage tracking, testing, and governance controls to ensure reliable and trustworthy experiment results.</p><p>·      Develop production-ready deployment workflows, CI/CD pipelines, observability solutions, and operational processes for data products and services.</p><p>·      Collaborate with Product Managers, Software Engineers, Data Scientists, and Analytics teams to translate business requirements into scalable technical solutions.</p><p>·      Drive best practices for data architecture, engineering standards, experimentation methodologies, and platform reliability.</p><p>·      Mentor engineers and promote a culture of technical excellence, innovation, experimentation, and continuous improvement.</p>

<p><strong>Core Qualifications:</strong></p><p>·      Bachelor&#39;s degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related technical discipline.</p><p>·      7+ years of experience in Data Engineering, Analytics Engineering, Data Platform Engineering, or related fields.</p><p>·      Strong experience designing, building, and supporting large-scale distributed data pipelines and data platforms.</p><p>·      Deep understanding of data modeling, ETL/ELT architectures, data warehousing, lakehouse technologies, and streaming data systems.</p><p>·      Hands-on experience building data solutions that support experimentation, product analytics, personalization, customer insights, or machine learning initiatives.</p><p>·      Advanced proficiency in SQL and Python.</p><p>·      Experience with modern data engineering technologies such as Databricks, Snowflake, Apache Spark, Kafka, Airflow, or comparable platforms.</p><p>·      Experience implementing automated testing, monitoring, data quality frameworks, observability, and governance processes.</p><p>·      Strong knowledge of cloud-based data ecosystems and distributed computing environments.</p><p>·      Ability to communicate complex technical concepts to both technical and non-technical stakeholders.</p><p>·      Proven ability to lead large-scale technical initiatives and deliver highly reliable production-grade data solutions.</p>

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