REMOTE GCP Data Engineer/Architect

Our leading entertainment client is expanding their data team and seeking a Data Engineer with deep expertise in GCP, Big Data, Python, SQL, DBT, and ERD architecture. This cross-functional team operates across three core areas: AI/ML, Data Engineering, and Data Analytics.

• Collaborate with stakeholders across subscription, viewership, marketing, paid media, CRM, and more. * Support data visualization initiatives and ensure data is accessible and actionable. * Work in a highly collaborative environment that values fast learners and team players. Spend approximately 80% of your time in hands-on development using Python and SQL.

Team Dynamic: Data Analytics Engineering (Approx. 80% of time) - Primary Focus: Analyze and maintain data pipelines, conduct root-cause analysis to resolve data-related issues, and create data models leveraging DBT and Medallion architecture. Tools & Skills: * Proficient in Python and SQL for pipeline development. * Initially focused on learning and maintaining existing pipelines, with a gradual transition to building new ones. Mindset: Business-oriented with a strong analytical approach.

AI/ML Initiatives (Approx. 5% of time) Objective: Support AI and machine learning efforts using modern platforms such as Vertex AI. Scope: Limited involvement, primarily assisting with existing initiatives and tools. Data Engineering (Approx. 15% of time) Responsibilities: Design and implement scalable data models, pipelines, and architecture. Technical Stack: Heavy use of Python and SQL to ensure robust and efficient data infrastructure.

• 10+ years in a Data Architect role, with a strong focus on data modeling in Big Data environments (100TB+). * Advanced proficiency in Python and SQL for data mining, pipeline development, segmentation, and orchestration. * Deep experience with GCP, including BigQuery, GCS Buckets, IAM, Google Cloud Storage (GCS), Cloud Function, Composer, and VertexAI. * Proven ability to analyze and troubleshoot complex data pipelines through root-cause analysis. * Hands-on experience using DBT for data modeling and transformation workflows. Strong understanding and application of ERD architecture in enterprise data systems.