Principal Data Engineer – Architect
| Company | The Walt Disney Company |
|---|---|
| Location | Seattle, WA, USA, Orlando, FL, USA, San Francisco, CA, USA, Bristol, CT, USA, New York, NY, USA |
| Salary | $159800 – $246400 |
| Type | Full-Time |
| Degrees | |
| Experience Level | Expert or higher |
Requirements
- At least 10+ years of experience in data architecture, engineering, or related field
- Expertise in cloud-based data platforms (AWS, GCP, Azure) and big data technologies (Hadoop, Spark, Kafka)
- Expertise in MPP and SaaS Data Products like Snowflake, Redshift etc.
- Strong knowledge of database design, SQL, and data warehousing principles
- Proven ability to lead complex projects and cross-functional teams
- Excellent problem-solving, communication, and leadership skills
Responsibilities
- Design and develop scalable, high-performance data architecture that supports both operational and analytical use cases.
- Lead the integration of new data management technologies and software engineering tools into existing structures.
- Collaborate with cross-functional teams including product management, software engineers, data scientists, and other stakeholders to align architecture with business requirements.
- Ensure data security, compliance, and privacy standards are met in accordance with company policies and regulations.
- Drive innovation in data processing and analytics, exploring emerging technologies and methodologies.
- Provide technical leadership and mentorship to the data architecture platform team.
- Oversee the documentation and communication of architectural designs and standards.
Preferred Qualifications
- Experience in the media/entertainment industry.
- Knowledge of streaming data platforms and real-time analytics.
- Familiarity with GDPR, CCPA, and other data privacy regulations.
- Experience with data modeling, ETL processes, and data integration tools.
- Experience with building SDLC for developing and implementing cost-effective large-scale data platforms from real-time/batch ingestion to delivering analytics feedback and reporting to consumers.
- Understanding different file format (parquet, ORC etc.) and table format (iceberg, delta etc.) and how to enable them if different data catalogs.