Senior Data Architect 21605-1

Job Description

Job 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-native 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-native 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