Staff Marketing Technology Engineer

Responsibilities

• Own and evolve a BigQuery marketing data warehouse with dbt-based transformations.
• Design and maintain batch and streaming ETL/ELT pipelines integrating diverse data sources and APIs.
• Design, build, and deploy Google Cloud applications and AI agents, including backends and lightweight frontends/UIs.
• Develop AI-powered tools that enable Marketing, Product, and other teams to self-serve automation.
• Apply AI to automate data-engineering work.
• Maintain engineering standards across an AI-assisted codebase, including Git workflows, code review, semantic versioning, automated testing, and CI/CD.
• Own data security and governance, including IAM, secrets, PII handling, BigQuery row- and column-level security, and AI safety guardrails.
• Collaborate with Marketing, Finance, Sales, Marketing Operations, analysts, and BI specialists to resolve data discrepancies through root-cause analysis.
• Shape the marketing technology and AI platform stack and provide architectural direction.
• Assess and mitigate risks affecting delivery, quality, stability, performance, and reliability.
• Serve as a subject-matter expert in data architecture, AI application engineering, and marketing technology.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
• 5+ years of data engineering experience, with breadth in software or AI application development.
• Strong software-engineering fundamentals, including Git, code review, automated testing, and CI/CD.
• Experience deploying applications on Google Cloud, such as Cloud Run, Cloud Functions, or GKE.
• Experience with Docker and infrastructure as code, such as Terraform.
• Experience building and deploying AI/LLM applications and agents, such as Vertex AI, Agent Builder, LangChain, or LangGraph.
• Experience with API design, such as FastAPI, and evaluating AI-system reliability.
• Expertise in SQL and Python.
• Experience designing ETL/ELT pipelines and integrating APIs.
• Required experience with BigQuery, dbt, and data-warehouse modeling.
• Knowledge of IAM, least-privilege access, secret management, and sensitive/PII data handling.
• Experience with cloud environments; GCP is preferred.
• Excellent written and verbal communication skills.

Nice-to-haves

• AWS or Azure experience.
• Familiarity with Fivetran.
• Familiarity with content management, CRM, experience management, email marketing, and tracking tools.
• Familiarity with Power BI or Tableau.

Compensation and Benefits

• Eligibility for two bonus plans.
• Comprehensive medical and dental benefits based on country of location.
• Retirement savings programs.
• Generous time off.
• New hire equipment allowance.
• Monthly flex allowance.
• Flexible remote-first work arrangements.