Senior Data Engineer, Growth Acquisition (Growth & Marketing Data)

Overview

Senior Data Engineer embedded in Growth Org within the User Life Cycle team, building the data foundation for marketing measurement, Marketing Mix Modeling, attribution and end-to-end funnel analytics.

What you'll do

• Design, build and operate reliable batch and streaming pipelines that unify paid, owned and organic marketing data (spend, impressions, installs, sessions, conversions) with in-platform user behavior.
• Own the data foundation for MMM by building well-documented, versioned, analysis-ready datasets and backfills that Data Science can use to train, refresh and validate models on a regular cadence.
• Partner with Marketing and Data Science to build attribution and funnel data products, and to define shared metrics (acquisition, activation, retention, reactivation, LTV).
• Architect event taxonomies and logging standards for acquisition and lifecycle events, and influence client and server instrumentation across product surfaces.
• Integrate with ad channel platforms, mobile measurement partners and other third-party sources, with strong attention to data quality, freshness, identity resolution and privacy-safe design.
• Set standards for table design, data quality monitoring, observability, lineage and documentation used across the Growth and Marketing space.
• Support experimentation and incrementality work (geo tests, holdouts, lift studies) by making experiment data easy to join to spend and outcomes.
• Mentor other engineers, raise the bar on data practices, and collaborate with Data Engineering, Data Infrastructure and ML Platform teams to leverage shared tooling.
• Work with partner teams across Roblox to make sure the measurement approach respects user privacy and safety and reflects community-first values.

What you'll need

• 8+ years of industry experience as a data engineer or data-focused software engineer building scalable batch and streaming pipelines.
• Proficiency in SQL and Python, PySpark or Scala.
• Experience with orchestration tools (Airflow, Dagster or similar).
• Experience with large-scale data processing (Spark, Flink, Kafka or similar), including multi-terabyte datasets.
• Strong data modeling skills, having designed dimensional or event-based models that analysts and data scientists rely on every day.
• Experience working directly with business and data science partners to turn ambiguous questions into durable data products.
• Experience with at least one major cloud platform (AWS, GCP or Azure) and modern warehouse or lakehouse technologies.
• Comfort with standard software practices: code review, CI/CD, testing and monitoring of data pipelines.

Nice to have

• Hands-on exposure to marketing measurement: MMM (for example Robyn, Meridian, PyMC-Marketing or in-house models), attribution, incrementality or experimentation platforms.
• Experience with marketing and ad data sources (ad platform APIs, mobile measurement partners, CRM or lifecycle tooling) and with identity resolution.
• Experience with data privacy constraints in measurement (consent, aggregation, clean rooms, differential privacy).
• Experience in consumer products with a growth, ads, personalization or lifecycle focus.

Details

• Location: headquarters in San Mateo, CA.
• Office schedule: onsite Tuesday, Wednesday and Thursday, with optional presence on Monday and Friday (unless otherwise noted).
• Reports directly to the Engineering Director.
• Annual base salary range: $243,290 to $295,250 USD.
• For US based roles only: the Company may not be able to employ candidates who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.