Data Scientist

🕒 February 6

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Xsolla

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2005

🎮 Gaming

🛍️ eCommerce

☁️ SaaS

Gaming • eCommerce • SaaS

Xsolla is a company specializing in game commerce solutions. It provides tools and services that empower video game developers to monetize, distribute, and fund their games, helping them to increase revenue at any stage of development. Xsolla offers a wide range of solutions such as customizable web shops, payment processing, fraud prevention, and social packages to enhance player engagement. With over 19 years of experience in the video game industry, Xsolla collaborates with developers and publishers globally to manage compliance, taxes, and operational complexities, allowing them to focus on connecting with their players. Their services are designed to work with popular game development platforms like Unity, Unreal, and Cocos Creator, supporting a wide array of local payment methods worldwide.

📋 Description

• Architecture & Development • Design, build, and optimize data pipelines and ETL workflows in Snowflake using Snowpark, Streams/Tasks, and Snowpipe. • Develop scalable data models, Algorithm supporting user 360 views, churn prediction, and recommendation engine inputs. • Lead integration across data sources: MySQL, BigQuery, Redis, Kafka, GCP Storage, and API Gateway. • Implement CI/CD for data pipelines using Git, dbt, and automated testing. • Define data quality checks and auditing pipelines for ingestion and transformation layers. • Leadership & Collaboration • Mentor and guide junior data engineers on data modeling, performance tuning, and Snowflake best practices. • Partner with Data Science, ML, and Backend teams to productionize machine learning features in Snowflake. • Work closely with Legal, Security, and Infrastructure teams to ensure compliance, privacy, and governance of user data (PII). • Collaborate with the Director of Data Platforms and product stakeholders to translate business requirements into technical specifications. • Performance & Scalability • Tune algorithm performance. • Establish data partitioning, clustering, and materialized views for fast query execution. • Build dashboards and monitors for pipeline health, job success, and data latency metrics (e.g., via Looker, Tableau, or Snowsight). • Governance & Best Practices • Establish and enforce naming conventions, data lineage, and metadata standards across schemas. • Lead code reviews, enforce documentation standards, and manage schema versioning. • Contribute to the company’s evolving data mesh and streaming architecture vision.

🎯 Requirements

• 5+ years of experience in Data Scientist, with **3+ years in Spark framework**. • Strong SQL and Python skills, with proven experience building **ETL/ELT** at scale. • Deep understanding of algorithm** performance tuning**, **query optimization**, and **warehouse orchestration**. • Experience with **data pipeline orchestration** (Airflow, Prefect, dbt, or similar). • Solid understanding of **data modeling** (Kimball, Data Vault, or hybrid). • Proficiency in **Kafka**, **GCP**, or **AWS** for real-time or batch ingestion. • Familiarity with **API-based data integration** and **microservice architectures**. • **Preferred** • Experience lead **machine learning teams** or/and deploying **ML feature pipelines**. • Background in **ad-tech, gaming, or e-commerce** recommendation systems. • Familiarity with **data contracts** and **feature stores** (Feast, Tecton, or custom-built). • Experience managing small data engineering teams and setting technical direction. • Strong ownership and ability to work autonomously in a fast-paced environment. • Excellent cross-functional communication — can translate between engineering and business. • Hands-on problem solver who balances velocity with reliability. • Collaborative mentor who raises the bar for team quality and discipline