Posted today · be early
[REMOTE] Data Engineer
CrazyGames
WorldwideremotePosted 1 day ago
Skill Required
Data-EngineeringData-InfrastructureAnalytics-EngineeringBackend-EngineeringProductRemote-Data-EngineerRemote-Data-EngineeringData-EngineerData EngineerETLEngineeringanalyticsRedshiftbuildingGenerative AISQLAWSandAIFulltime
Key highlights
- The role is for an experienced Data Engineer, available as full or hybrid remote, based in Europe
- CrazyGames is one of the world’s largest casual gaming platforms, with over 60 million monthly visitors and more than 300 million monthly gameplays
- The platform is enjoyed by 3 million+ players every day
- The core of the role is managing the end-to-end data pipeline for millions of daily users
- A key 3-month performance target is to identify pipeline improvements that cut costs or boost time efficiency by 5%
- Benefits include flexible working hours and location, plus 1-2 fully paid annual team weeks with covered flights and accommodation
Role overview
CrazyGames.com, one of the world’s largest casual gaming platforms with over 60 million monthly visitors, is hiring a full or hybrid remote experienced Data Engineer based in Europe. The core of the role involves managing the end-to-end data pipeline for millions of daily users, from initial data collection through cleanup and aggregation, to make data accessible for analysts and internal teams to derive actionable insights. You will report directly to the Head of Data and collaborate closely with cross-functional Data and Engineering teams.
Responsibilities
- Maintain and improve the infrastructure that collects, stores, and transforms the company's analytics data, ensuring it remains reliable and cost-efficient (covering ingestion, cleanup, summarization, and aggregation of data)
- Monitor the health of the data pipeline and resolve performance issues
- Build new intermediate tables in the company data lake to simplify information consumption for data users
- Collaborate with Data Scientists to improve the quality of the datasets they use for their work
- Optimize the data ingestion process to improve cost-efficiency
- Develop and support a semantic layer for AI-driven data analyses
Requirements
- Ability to identify areas of improvement in data processes and deliver results autonomously
- Expert-level SQL proficiency
- Strong preference for open, efficient, and to-the-point communication, with prior professional experience working remotely
- High intelligence, efficiency, strong organizational skills, and attention to detail
- Relevant professional experience working at a company with a large data lake serving an extensive user base
- Familiarity with leveraging AI for efficient work, while maintaining strong critical thinking skills
Nice to have
- Experience with AWS infrastructure, especially Amazon Redshift
- Professional experience in the Gaming, Media, or Entertainment sector
Benefits
- Opportunity to join the Data team alongside Data Analysts and Scientists
- Collaborate with an elite engineering team of 15+ experienced engineers
- Work with a modern tech stack operating at massive scale (processing over 300 million gameplays per month across global user device types)
- High level of responsibility and autonomy; the company hires only experts and trusts them to deliver excellent results
- Flexible working hours and location, with performance as the core measure of success
- 1-2 paid team weeks per year, with flights and accommodation covered for in-person team events
- Opportunity to play games as part of work responsibilities
Additional details
- Reporting structure: The role reports directly to the Head of Data and collaborates closely with cross-functional Data and Engineering teams
- Key performance milestones for the role: Within 1 month of starting, gain a clear understanding of every step of the data pipeline from data ingestion to end usage in dashboards; Within 3 months of starting, identify areas of pipeline improvement and achieve a 5% reduction in costs or improvement in time efficiency; Within 6 months of starting, deploy multiple changes to the data pipeline and autonomously plan future work; Within 12 months of starting, fully own the data pipeline and successfully take over all related responsibilities from existing Engineers
- Screening rule: Glaring use of GenAI technologies to fill in screening questions will result in disqualification
- Original posting platform: The role was originally posted on Himalayas