Das ist der Job
Focus on extending and operating the company’s Elastic Hierarchy framework.
Darum lohnt es sich
Collaborate with analytics, ML, and product teams to deliver reliable, business-ready datasets. Senior Data Engineer
Design, build, and maintain scalable data systems to support analytics and machine learning in a hybrid SaaS and on-premise environment. Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines using Python.
Process and integrate data from multiple formats and sources (JSON, CSV, XML). Build and manage data transformations and orchestration workflows using dbt and orchestration tools such as Airflow, Prefect, or Dagster. Enforce data governance, quality, and security standards. Extend, maintain, and optimize the Elastic Hierarchy data framework.
Support data operations in SaaS and hybrid on-premise environments. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. Strong Python development skills. Experience with AWS data services (S3, Glue, Lambda, EMR, EC2, Redshift, RDS). Hands‑on experience with Snowflake, MongoDB, and PostgreSQL.
Experience using dbt and at least one orchestration tool.
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