Senior Data Engineer, Marketing Analytics (R-19206)

What we offer

• Generous paid time off in your first year, with increases as tenure progresses.
• Up to 16 weeks of 100 percent paid parental leave after one year of employment.
• Paid sick time to care for yourself or family members.
• Education assistance and extensive training resources.
• Do Good Program with paid volunteer days and donation matching.
• Competitive 401(k) with company matching.
• Health and wellness benefits, including discounted Wellhub membership rates.
• Medical, dental, and vision insurance for you, spouse or partner, and dependents.

Responsibilities

• Translate marketing and measurement requirements into scalable technical solutions, recommending patterns that improve maintainability and speed of change.
• Own day to day platform health by monitoring scheduled workflows, investigating failures, restoring services, and preventing repeat issues.
• Define and track operational KPIs such as data freshness, latency, completeness, error rates, and cost; drive improvements against 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.

Requirements

• 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 with modern data warehouses and enterprise data platforms such as BigQuery, Snowflake, Redshift, or SQL Server.
• Comfort operating configuration driven workflows and orchestration frameworks (for example YAML based pipelines).
• Experience designing and supporting API based data integrations with robust authentication and error handling.
• Preferred experience with SQL based transformation frameworks such as 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 is an advantage.
• Proficiency in Microsoft Office Suites.
• Ownership mindset; problem solving orientation, curiosity, proactive collaboration with teams to drive success.
• Continuous growth mindset with ongoing learning through stakeholder relationships and formal programs.
• Where applicable, fluency in English and languages relevant to the working market.

Technologies

• SQL, Python
• BigQuery, Snowflake, Redshift, SQL Server
• dbt, Dataform
• YAML
• Google Cloud Platform (GCP)
• Microsoft Office Suite

Physical Requirements

• Ability to sit, speak, and operate a computer for extended periods
• Ability to handle pressure and resolve conflicts
• Ability to work day, evening, or weekend hours as needed

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Equal Employment Opportunity (EEO)

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AI in Hiring

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