FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and optimizing large-scale data solutions within Google Cloud Platform, with a strong focus on data analytics, automation, and security. Proficient in developing scalable data pipelines and integrating AI/ML technologies for enhanced data processing and visualization.
Highest-signal resume keywords
Google BigQuery ArchitectureGCP Dataflow ServicesPython Coding ExpertiseCloud SQL AdministrationGoogle Cloud Professional Data Engineer Certification
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data AnalyticsSQL QueriesData Pipeline DevelopmentAutomation SolutionsData ModelingAI/ML IntegrationEvent-Driven MicroservicesData VisualizationData GovernanceDevSecOps Automation
Soft Skills
LeadershipMentoringCommunicationCollaborationProblem-Solving
Tools & Technologies
GCP Cloud RunGCP Cloud FunctionsPostgreSQLLookerTableauApache BeamAirflowDbtCI/CD PipelinesELK
Certifications & Qualifications
Google Cloud Professional Data EngineerGoogle Cloud Professional Cloud Architect
Industry Keywords
Threat ManagementRisk ManagementVulnerability ManagementData Privacy StandardsAgile Methodologies
Tech Stack
Tools & technologiesAirflowApacheBigQueryCloudETLGoogle Cloud PlatformMicroservicesPostgresPythonSQLTableau
About the role
Key responsibilities & impact- Architect and optimize large-scale security data repositories in Google BigQuery
- Design and implement low-latency batch and streaming data pipelines using GCP Dataflow and Apache Beam
- Design and maintain optimized GCP Cloud SQL data layers using PostgreSQL
- Lead analytics engineers technically in architecting and deploying production-grade automation solutions
- Build scalable, event-driven microservices and high-performance APIs with GCP Cloud Run and Cloud Functions
- Integrate AI/ML automation, including Vertex AI and LLMs, for data extraction, metadata tagging, and pipeline orchestration
- Transition standard visualization to a scalable data product model
- Establish and maintain a Looker dashboard catalog for enterprise risk forecasting
- Develop and maintain a standardized semantic layer using LookML
- Build business cases and data models for Enterprise Security Data Analysis and Reporting
- Drive long-term security investments and collaborate with cross-functional SRE and backend teams
Requirements
What you’ll need- Bachelor degree in Computer Science/Information Systems or an equivalent combination of education and work experience
- Six to eight years of professional experience in data analytics, business analysis or comparable analytics position
- Proven experience architecting and developing solutions within Google Cloud Platform, specifically Cloud Run and Cloud Functions
- Deep technical mastery of Google BigQuery architecture, including nested/repeated fields, materialized views, and BigQuery Omni or ML capabilities
- Hands-on experience building streaming and batch data processing pipelines using GCP Dataflow services
- Advanced proficiency in complex, optimized SQL queries and GCP Cloud SQL administration and optimization using PostgreSQL
- Strong hands-on coding expertise in Python for advanced data analysis, data mining, DevSecOps automation, and pipeline orchestration
- Familiarity with deploying AI-driven automation workflows
- Experience with Tableau, Looker, or Thoughtspot
- Experience embedding Looker visualizations into serverless applications or enterprise API frameworks is highly desirable
- Ability to write SQL against a relational database to analyze and test data
- Experience with Airflow, dbt, and CI/CD pipelines applied directly to data engineering
- Knowledge of Threat, Risk and Vulnerability Management is an added advantage
- Knowledge of OAuth, OIDC, API Gateways, and data privacy/governance standards
- Cloud Certifications
- Professional Google Cloud Professional Data Engineer or Professional Cloud Architect certification is an added qualification
- Experience in technology leadership, architecture, and Agile methodologies
- Experience with DevOps CI/CD processes
- Experience mentoring and coaching diverse teams
- Experience identifying, analyzing, and finding RCA for errors
- Experience with Postgres, Looker, ELK, and ETL tools
- Good presentation and communication skills
Benefits
Comp & perks- Work from home and assigned office days in a hybrid arrangement
- Career growth and development opportunities
- Learning and professional growth in a collaborative community
- Scheduled weekly hours: 40