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Xsolla

Xsolla's video game business engine helps game developers and publishers operate more efficiently and sell more games.

Engineering Manager, Data

Engineering ManagerEngineering ManagerFull TimeRemoteSeniorTeam 201-500Since 2005H1B SponsorCompany SiteLinkedIn

Location

Canada

Posted

22 days ago

Salary

$120K - $160K / year

Seniority

Senior

Bachelor Degree5 yrs expEnglishAirflowBigQuerySpark

Job Description

Engineering Manager, Data

Xsolla

• Lead and grow a high-performing, distributed team of data scientists, ML engineers, and data platform engineers • Define and execute the data science and ad tech roadmap, advancing initiatives in user modeling, campaign optimization, targeting, and personalization • Architect and manage ML pipelines and experimentation frameworks, including feature engineering, training pipelines, model serving, A/B testing, and causal inference systems • Oversee real-time pipelines for ad events (e.g., impressions, clicks, conversions), enabling responsive attribution and performance optimization • Collaborate with Product, Growth, and Marketing to develop audience scoring, LTV/churn models, and incrementality testing for media measurement and bidding efficiency • Ensure scalable, privacy-compliant data infrastructure aligned with GDPR, CCPA, and ATT, including support for SKAdNetwork, CMPs, and identity frameworks • Foster engineering excellence with a focus on reproducibility, model evaluation, observability, and model lifecycle management • Drive a strong feedback loop between experimentation and business outcomes, translating data science insights into product and go-to-market wins • Mentor engineers and scientists on career development, technical depth, and cross-functional leadership

Job Requirements

  • 5+ years of experience in software/data engineering or applied data science
  • 3+ years managing technical teams in ML, analytics, or ad tech domains
  • Deep understanding of machine learning and statistical modeling, including regression, classification, causal inference, uplift modeling, and forecasting
  • Hands-on experience with ML/data platforms such as Snowflake, BigQuery, Spark, Airflow, dbt, MLFlow, and feature stores
  • Proven experience in architecting and deploying end-to-end ML systems into production (batch and real-time)
  • Knowledge of ad tech ecosystems, including campaign hierarchies, attribution models (multi-touch, view-through), and creative performance tracking
  • Familiarity with audience management, segmentation, and personalization frameworks in programmatic or CRM marketing
  • Experience with privacy-preserving measurement, including support for SKAdNetwork, GAID/IDFA deprecation, and consent systems
  • Bachelor’s or Master’s in Computer Science, Engineering, Statistics, or a related field
  • PhD is a plus

Benefits

  • medical, dental, and vision
  • PTO
  • a personalized career roadmap for each employee
  • investing in professional development through training and educational opportunities

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