Architect Lead
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SeniorFull-time
#448804·Dodano wczoraj·0
Źródło: nofluffjobs.comTech Stack / Keywords
Data engineeringPythonSQLData modellingCloud platformAWS S3KinesisECSAWS ECSETLAirflowInfrastructure as CodeAWS
Wymagania
- 7+ years of experience in Data Engineering, including experience as a Tech Lead, Architect, Staff or Principal Data Engineer.
- A proven track record of designing and building data platforms end-to-end.
- Strong architectural skills and the ability to make, document, and defend technical decisions.
- Senior-level Python skills with direct implementation contributions.
- Strong SQL skills and a solid understanding of data modelling, data warehousing, schema design, partitioning, and versioning.
- Strong experience with cloud platforms, preferably AWS, including technologies such as S3, Kinesis, ECS, and Athena.
- Experience with modern data stack technologies, e.g. dbt.
- Hands-on experience with ETL orchestration tools such as Airflow or similar.
- Experience with Infrastructure as Code.
- Experience hiring, mentoring, and developing engineering teams.
- Excellent communication and collaboration skills.
Nice to have:
- Experience in gaming or other high-scale consumer environments.
- Experience with billions of events, real-time or near-real-time data, large-scale consumer products, product analytics, LiveOps, and high-volume data platforms.
Obowiązki
- Define and own the end-to-end architecture of the data platform.
- Establish the technical foundations, standards, and best practices for a platform built from the ground up.
- Make, document, and defend key architectural and technology decisions, balancing scalability, performance, cost, and team capacity.
- Design solutions capable of supporting hundreds of millions of users and billions of events per day.
- Build core parts of the platform hands-on and remain actively involved in implementation.
- Partner with Product, Game, Analytics, and Marketing leadership to translate business needs into a clear platform roadmap.
- Establish engineering practices, code review standards, and operational discipline.
- Hire, mentor, and grow the Data Engineering team.
- Ensure the platform is scalable, reliable, maintainable, and cost-efficient.
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