Enterprise Data Architect

About Us

At Cast & Crew, we’ve empowered creativity and supported the global entertainment industry for decades. Together with our family of brands - Backstage, CAPS, Checks & Balances, Final Draft, Media Services, Sargent-Disc, and The TEAM Companies – we operate as a combined entertainment technology and services provider offering industry standard screenwriting accounting software, digital payroll products, data & reporting, and a host of creative tools.  The industry continues to move faster than ever, and the need for our expertise, our technology, and our people has never been greater.  We are a production’s best ally every step of the way. #OneCastOneCrew

Position Summary
We are seeking an experienced Enterprise Data Architect to lead the design and evolution of our enterprise data architecture. This role will be pivotal in shaping and implementing a modern, AI-driven data platform that supports business intelligence, analytics, operational systems, and data-driven innovation. The ideal candidate combines deep technical knowledge with strategic vision and has hands-on experience designing scalable, secure, and resilient data ecosystems in hybrid and cloud environments.

This individual will play a key role in consolidating fragmented and legacy large-scale payroll databases into a unified modern data platform. They will help architect the next-generation AI and data-driven payroll platform, enabling intelligent automation, advanced analytics, and real-time business insights across the enterprise.

Key Responsibilities

• Lead the architecture and design of enterprise-wide data platforms, data lakes, and data warehouses across cloud and on-prem environments.
• Architect and execute a strategy to migrate and consolidate legacy monolithic and siloed data systems into a cloud-native modern data platform.
• Define and govern data architecture standards, data modeling practices, and metadata management strategies.
• Design and oversee the implementation of high-performance, scalable, and secure databases for operational and analytical workloads.
• Partner with data engineering, analytics, and AI/ML teams to enable robust data pipelines, real-time streaming, and advanced analytics.
• Evaluate and implement modern data platform technologies, including cloud-native services, AI-enhanced data ops, and data mesh/data fabric architectures.
• Develop and enforce data governance, data quality, and compliance strategies.
• Provide architectural leadership in planning, roadmapping, and execution of enterprise data initiatives.
• Support data product thinking and advise cross-functional teams on best practices in data architecture and platform usage.

Required Skills and Experience

• 10+ years of experience in data architecture, data engineering, or related roles, with a focus on large-scale enterprise environments.
• Proven experience in consolidating legacy systems and replatforming towards cloud-native, modern data platforms.
• Strong expertise in enterprise data modeling (conceptual, logical, physical), data normalization/denormalization, schema design, and performance tuning.
• Hands-on experience with cloud data platforms such as Snowflake, AWS (Redshift, S3, Glue, Lake Formation, Athena, EMR), Google Cloud (BigQuery, Dataflow, Pub/Sub) or Azure (Synapse, Data Factory, Databricks, ADLS).
• Deep knowledge of relational and NoSQL databases: PostgreSQL, MS SQL Server, Oracle, MySQL, MongoDB, Cassandra, DynamoDB.
• Experience with modern data stack tools: ETL/ELT (dbt, Fivetran, Informatica), Streaming (Apache Kafka, Spark Streaming, Flink), Orchestration (Airflow, Dagster).
• Familiarity with data lakehouse architectures and technologies (e.g., Delta Lake, Iceberg, Hudi).
• Experience enabling AI/ML pipelines, feature stores, and real-time inference systems.
• Expertise in data governance, privacy, and compliance frameworks (e.g., GDPR, CCPA, HIPAA).
• Strong programming and scripting skills: SQL, Python, Scala, .net core, or Java.
• Excellent communication and collaboration skills with ability to work cross-functionally.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• Cloud certifications (AWS, Azure, GCP) related to data architecture or engineering.
• Experience in architecting modern payroll, HR, or financial platforms is highly desirable.
• Understanding of AI-driven data quality tools, metadata automation, and semantic layers.
• Knowledge of data mesh, data fabric, and domain-oriented data services.

Special Work Conditions    

• Sedentary – In