Senior Data Architect 21605-1

Job DescriptionJob Description

Apply now: Senior Data Architect, location is Hybrid (Burbank, CA). The start date is August 26, 2025 or two weeks from offer for this 1-year contract position.

Job Title: Senior Data Architect
Location-Type: Hybrid (Tues–Thurs onsite)
Start Date Is: August 26, 2025 or two weeks from offer
Duration: 1 year contract
Compensation Range: $90.00/hr – $110.00/hr W2

Job Description:
Design, build, and govern scalable, reusable, cloud- data architectures and pipelines to power analytics, forecasting, and AI-driven insights, ensuring alignment with enterprise governance standards.

Day-to-Day Responsibilities:

• Define and maintain canonical data models, semantic layer specifications, and entity relationships for consistent use across domains

• Develop logical and physical data models supporting real-time analytics and forecasting

• Architect resilient, high-performance batch and streaming pipelines using AWS- services (Glue, Kinesis, Lambda, Step Functions)

• Partner with governance teams to embed metadata, lineage, access controls, and data quality into the design process

• Implement APIs, semantic models, and reusable data services for multi-team adoption

• Collaborate with product pods, cloud architects, and engineers to deliver shared services and resolve semantic conflicts

• Enable ML/AI-ready pipelines and accelerate model development by structuring data for analytics use cases

Requirements:

• Must-Haves:

  • 7 years' experience designing and delivering data architecture for cloud-based platforms

  • Deep AWS expertise (Glue, Lambda, Step Functions, Lake Formation)

  • Proficiency with modern tooling (Snowflake, Databricks, Informatica)

  • Proven ability to design scalable, reusable canonical and semantic data models

  • Hands-on pipeline design and orchestration for batch and real-time processing

  • Knowledge of governance, lineage, and quality best practices

  • Strong cross-functional collaboration skills and ability to translate architecture decisions across technical and business audiences

• Nice-to-Haves:

  • Experience in media, entertainment, or financial analytics

  • MLOps and AI/ML data enablement experience