Engineering Manager, Data

Xsolla seeks a strategic, hands-on Engineering Manager to lead data and machine learning initiatives, oversee ad-tech and experimentation platforms, ensure scalable privacy-compliant infrastructure, and connect data science outcomes to product and business results.

Responsibilities

  • 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 across 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.
  • Oversee real-time ad-event pipelines for attribution and performance optimization.
  • Collaborate with Product, Growth, and Marketing on audience scoring, LTV/churn models, and incrementality testing.
  • Ensure scalable, privacy-compliant infrastructure aligned with GDPR, CCPA, and ATT, including SKAdNetwork, CMPs, and identity frameworks.
  • Promote reproducibility, model evaluation, observability, and model lifecycle management.
  • Translate data science insights into product and go-to-market outcomes.
  • Mentor engineers and scientists on technical depth, career development, and leadership.

Requirements

  • 5+ years in software or data engineering or applied data science, including 3+ years managing technical teams in ML, analytics, or ad tech.
  • Deep knowledge of machine learning and statistical modeling, including regression, classification, causal inference, uplift modeling, and forecasting.
  • Hands-on experience with Snowflake, BigQuery, Spark, Airflow, dbt, MLFlow, and feature stores.
  • Experience architecting and deploying batch and real-time ML systems into production.
  • Knowledge of ad-tech ecosystems, attribution models, campaign hierarchies, and creative performance tracking.
  • Familiarity with audience management, segmentation, and personalization frameworks.
  • Experience with privacy-preserving measurement, SKAdNetwork, GAID/IDFA deprecation, and consent systems.
  • Excellent leadership, communication, and stakeholder management skills.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field; PhD is a plus.

Benefits

  • Medical, dental, and vision insurance
  • PTO
  • Personalized career roadmap
  • Professional development through training and educational opportunities

See also

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