TL;DR

Senior Google Cloud Data Engineer (Data Engineering): Driving cybersecurity analytics and anomaly detection projects independently, ensuring timely delivery and high-quality outcomes. Focus on implementing machine learning models to identify potential intrusions and fraudulent patterns in network traffic.

Location: Onsite in New York City (Brooklyn area) 3 days per week, and remote 2 days per week. Candidates must be legally authorized to work in the United States and must hold either U.S. citizenship or lawful permanent resident (Green Card) status.

Salary: $170,000-240,000 annually

Company

Valtech is the experience innovation company that exists to unlock a better way to experience the world.

What you will do

  • Drive projects independently, ensuring timely delivery and high-quality outcomes.
  • Lead and execute projects related to cybersecurity, including anomaly detection in data to identify potential security threats.
  • Develop dashboards and visuals for operational and executive use, leveraging Looker Core and BigQuery.
  • Implement alerting systems to proactively detect anomalies and security issues.
  • Design and implement data ingestion and transformation pipelines leveraging Google Cloud Dataflow / Apache Beam and BigQuery for analytics and large-scale querying.
  • Build fault-tolerant, self-healing, adaptive, and highly accurate streaming and batch data pipelines on GCP.

Requirements

  • Candidates must be legally authorized to work in the United States and must hold either U.S. citizenship or lawful permanent resident (Green Card) status.
  • Strong expertise in Python and SQL.
  • Hands-on experience with Core GCP Data Stack: BigQuery, Dataflow (Apache Beam), and Pub/Sub.
  • Hands-on experience with Visualization & BI: Looker Core – Advanced proficiency in LookML.
  • Familiarity with Alerting Frameworks.
  • Ability to work independently and drive projects solo with minimal supervision.

Nice to have

  • Google Cloud Professional Data Engineer certification.
  • Google Professional Machine Learning Engineer certification.
  • Google Cloud Professional Cloud Architect certification.
  • Bachelor’s or Master’s degree in a quantitative or technical field.

Culture & Benefits

  • Flexibility, with remote and hybrid work options (country-dependent).
  • Career advancement, with international mobility and professional development programs.
  • Learning and development, with access to cutting-edge tools, training, and industry experts.
  • Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts.

Hiring process

  • Talent Acquisition team will review your application.
  • If your skills and experience align with the role, we’ll reach out for next steps.
  • Your CV should cover key information on relevant experiences and expertise.