Lead Data Engineer

We’re looking for a Lead Data Engineer to own and scale our end-to-end data infrastructure that powers marketing, monetization, and analytics across our gaming portfolio.You’ll design, build, and optimize data pipelines from Adjust, ad network APIs, and in-game data sources into our data stack. As a team leader, you’ll set the technical direction, establish best practices, and mentor other engineers to deliver reliable and scalable data systems.Key Responsibilities:Lead the architecture, design, and optimization of our data platform (AWS → Iceberg → StarRocks).Build and maintain ETL/ELT pipelines ingesting data from:Mobile Measurement Partners (MMPs) like AdjustAd network APIs (Meta, Google Ads, AppLovin, Unity Ads, IronSource, etc.)Monetization and in-app purchase data sourcesDefine and enforce data engineering best practices (testing, CI/CD, versioning, documentation).Collaborate with analysts, scientists, and marketing teams to design performant data models.Establish a data roadmap, ensuring scalability, cost-efficiency, and reliability.Implement data observability, alerting, and performance monitoring systems.Mentor and support junior data engineers, promoting high engineering standards.Requirements5+ years of experience in data engineering or related roles.Bachelor’s degree in a STEM field (Computer Science, Engineering, Mathematics, or related).Strong expertise with:AWS (S3, Glue, Lambda, Athena)Apache Iceberg or similar lakehouse technologies (Delta Lake, Hudi)StarRocks / CelerData, ClickHouse, or similar MPP systemsProficiency in Python for data processing and API integration.Strong SQL and data modeling skills.Hands-on experience integrating marketing and ad network APIs.Familiarity with Airflow, dbt, or other orchestration tools.Strong communication, leadership, and cross-functional collaboration skills.Nice to HaveExperience with real-time streaming (Kafka, Flink, Kinesis).Familiarity with BI tools (Power BI, Looker, DataLens).Experience in gaming analytics, user acquisition, or pLTV modeling.