17 set - Ega
Mentor Talent Acquisition
We are looking for a Data Engineer who enjoys building reliable data pipelines. You will helpPossiede le qualifiche e le competenze giuste per questo lavoro? Lo scopra qui sotto e invii la sua candidatura per essere preso/a in considerazione.design and operate scalable ELT processes that power analytics, reporting, and core product features. You are comfortable working with Python, SQL and AWS, understand modern data architecture patterns, and care about data quality, performance, and maintainability.Your responsibilitiesDesign, build and maintain scalable ELT pipelines.Implement and operate data workflows using AWS (Lambda, Step Functions, S3, Batch, etc.).Contribute to the evolution of our Data Platform architecture (Medallion architecture).Ensure data quality, consistency, and reliability across pipelines.Optimize data transformations for performance and cost efficiency.Collaborate with Backend and Frontend Engineers and Product to define data requirements.Monitor pipelines, troubleshoot issues and improve observability.Document data models,
transformations and architecture decisions.Your skillsStrong Python skills for data processing.Experience building ETL/ELT pipelines in production environments.Solid experience with AWS (especially Lambda, Step Functions, S3).Understanding of Medallion Architecture.Strong SQL skills and experience with dimensional data modeling.Experience working with structured and semi-structured data (JSON, CSV, Parquet, APIs).Understanding of data validation and data quality practices.Experience with Git and CI/CD.Nice to haveExperience with columnar databases (e.G. ClickHouse, Redshift, BigQuery).Familiarity with infrastructure-as-code (e.G. Terraform).Experience with Docker.You can expectBeing part of a highly motivated international team.High ownership and responsibility for your domain. xysqume A modern data stack and room to shape architecture decisions.A workplace in the heart of Vienna or remote options with quarterly office weeks in Vienna
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