Original listing text, shown exactly as published by the company.
Essential Key Responsibilities
Translate marketing and measurement requirements into scalable technical solutions, recommending implementation patterns that improve maintainability and speed of change.
- Own day-to-day platform health by monitoring scheduled workflows, investigating failures, restoring service, and preventing repeat issues.
- Define and track operational KPIs such as data freshness, latency, completeness, error rates, and cost; drive improvements against agreed SLAs.
- Maintain runbooks and production support processes, including release readiness and incident response, aligned with platform team practices.
- Design, build, and maintain scalable ELT/ETL pipelines that ingest and standardize marketing and revenue data into analytics-ready datasets.
- Implement and operationalize automated data quality controls, including validation checks, reconciliation routines, and anomaly detection.
- Own the platform intake process by triaging requests, proposing approaches, and communicating tradeoffs between accuracy, speed, and complexity.
- Partner with security, governance, privacy, and compliance stakeholders to ensure pipelines meet access control and data handling expectations.
Essential Skills and/or Certifications
Bachelor’s degree in Computer Science, Mathematics, Data Science or related field
- 8+ years of experience in data engineering, analytics engineering, or data platform roles, including hands-on ownership of production pipelines.
- Strong experience with SQL and Python, including data modeling across structured and semi-structured datasets.
- Experience working with modern data warehouses and enterprise data platforms (e.g., BigQuery, Snowflake, Redshift, SQL Server).
- Comfort operating configuration-driven workflows and orchestration frameworks (e.g., YAML-based pipelines).
- Experience designing and supporting API-based data integrations with robust authentication and error handling.
- Preferred experience with SQL-based transformation frameworks (e.g., dbt or Dataform).
- Familiarity with marketing measurement domains such as event tracking, campaign attribution, conversions, and revenue reconciliation.
- GCP Professional Data Engineer, Cloud Architect, Cloud Database Engineer, or Cloud Developer certification an advantage.
- Proficiency in Microsoft Office Suites Skills
- Show an ownership mindset in everything you do; be a problem solver, be curious and be inspired to take action, be proactive, seek ways to collaborate and connect with people and teams in support of driving success.
- Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs.
- Where applicable, fluency in English and languages relevant to the working market.
Physical Requirements
Ability to sit, speak and operate telephone and/or computer for long periods of time…
