Senior Analyst, Data Engineering
The Walt Disney Company
CloudETLInformaticaPythonSQL
Job Level
SeniorLead
Tech Stack
Amazon RedshiftAWSCloudPostgresPySparkTableau
About the role
- Lead architecture and evolution of Enterprise Unified Data Platform (UDP) to enable healthcare data modernization.
- Democratize access to healthcare administration, care management, and health informatics data while aligning to product-level UDP architecture.
- Serve as Enterprise UDP technical architect, aligning with Product UDP governance, security, and architecture.
- Design federated data architecture using virtualization tools to connect domain UDPs and external sources without duplicating datasets.
- Lead semantic layer architecture to unify attributes across data sources and enable access control, discovery, and execution.
- Architect and scale AWS-native components including S3, Redshift, Glue, Lambda, DMS, EventBridge, Athena, CloudTrail, CloudWatch, and KMS.
- Use PostgreSQL for reference/application data and PySpark for large-scale transformations.
- Drive data lake and lakehouse architecture for ingestion, storage, cataloging, and virtualization of structured/unstructured data.
- Enable self-service consumption via virtualized access integrated with Tableau, Power BI, and NLP-based query engines.
- Collaborate with product managers, platform engineers, and DevOps to ensure reusable, governed, secure cloud-native components.
- Support metadata management, data cataloging, RBAC, and auditability using AWS IAM, Glue Catalog, and related services.
- Evaluate and recommend emerging AWS/data technologies aligned to roadmap and federated principles.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- 10+ years of experience in data architecture and engineering, with 5+ years building and scaling solutions on AWS.
- Deep experience with AWS services: Glue, Redshift, S3, Lambda, DMS, Athena, IAM, CloudTrail, etc.
- Strong proficiency in PostgreSQL, PySpark, and big data transformation tools and frameworks.
- Demonstrated expertise in federated data architecture, data virtualization, and semantic data modeling.
- Solid understanding of healthcare data domains such as Medicaid eligibility, claims, provider, member, and care management.
- Proven track record aligning to platform-level architecture and governance standards, avoiding siloed or point-specific implementations.
- Skilled in data cataloging, lineage, access control, and data quality enforcement.
- Strong communication and collaboration skills in cross-functional, agile environments.
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