Responsibilities
- Architect and optimize large-scale security data repositories in Google BigQuery, including partitioning, clustering, storage tiering, nested and repeated fields, and materialized views.
- Design and implement batch and streaming data pipelines with GCP Dataflow and Apache Beam.
- Design and maintain optimized Cloud SQL data layers using the PostgreSQL engine.
- Lead analytics engineers technically in deploying automation solutions, serverless microservices, and APIs with Cloud Run and Cloud Functions.
- Identify and implement AI/ML automation for data extraction, metadata tagging, and pipeline orchestration.
- Develop a scalable security data product model and comprehensive Looker dashboard catalog for enterprise risk forecasting.
- Build and maintain standardized LookML semantic layers with consistent data access controls and reusable security-domain models.
- Develop business cases and data models for enterprise security data analysis and reporting.
- Secure cloud data delivery layers using OAuth, OIDC, API gateways, and privacy and governance standards.
Requirements
- Bachelor’s degree in Computer Science or Information Systems, or six or more years of work experience.
- Eight or more years of professional experience in data analytics, business analysis, or a comparable analytics position.
- Advanced Python and complex SQL skills, including hands-on administration and optimization of GCP Cloud SQL with PostgreSQL.
- Ability to write SQL against relational databases to analyze and test data.
- Experience with GCP, Cloud Run, Cloud Functions, BigQuery, and Dataflow for production data solutions.
- Experience with DataOps/DevSecOps orchestration tools such as Airflow and dbt applied to data engineering.
- Familiarity with AI-driven automation workflows and scalable application delivery.
- Experience with visualization platforms such as Tableau, Looker, or ThoughtSpot.
- Experience embedding Looker visualizations into serverless applications or enterprise API frameworks is highly desirable.
- Knowledge of Threat, Risk and Vulnerability Management is advantageous.
- Cloud certifications are required; Google Cloud Professional Data Engineer or Professional Cloud Architect certification is preferred.
- Experience with technology leadership, architecture, DevOps CI/CD processes, mentoring, stakeholder management, and cross-functional troubleshooting is preferred.
- Experience with analytical tools and databases such as PostgreSQL, Looker, ELK, and ETL tools is preferred.
Benefits
- Hybrid work arrangement with work-from-home flexibility and assigned office days determined by the manager.
- Full-time schedule of 40 hours per week.
Tech Stack
Categories
About Verizon
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