Data Engineer (Remote | Europe)

Mentor Talent Acquisition

Italia

Remoto

EUR 55.000 - 75.000

Tempo pieno

7 ore fa
Candidati tra i primi

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Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Descrizione del lavoro

Mentor Talent Acquisition is seeking a Data Engineer to design, build and maintain scalable ELT pipelines powering analytics, reporting, and core product features. You will work with Python, SQL and AWS, shaping modern data architecture with a focus on quality and performance.

You’ll implement AWS workflows, contribute to the Medallion architecture, optimize transformations for cost efficiency and collaborate with cross-functional teams to meet data needs. Remote-friendly with flexible options.

Competenze

  • Experience building ETL/ELT pipelines in production environments.
  • Strong SQL skills and experience with dimensional data modeling.
  • Solid experience with AWS (Lambda, Step Functions, S3).
  • Understanding of Medallion Architecture and data quality practices.
  • Experience with structured and semi-structured data (JSON, CSV, Parquet, APIs).
  • Experience with Git and CI/CD.

Mansioni

  • Design, build and maintain scalable ELT pipelines.
  • Implement and operate data workflows using AWS (Lambda, Step Functions, S3, Batch).
  • Contribute to the evolution of our Data Platform architecture (Medallion).
  • 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.
  • Experience building ETL/ELT pipelines in production environments.
  • Solid experience with AWS (Lambda, Step Functions, S3).
  • Understanding of Medallion Architecture.
  • Strong SQL skills and experience with dimensional data modeling.
  • Experience with structured and semi-structured data (JSON, CSV, Parquet, APIs).
  • Understanding of data validation and data quality practices.
  • Experience with Git and CI/CD.

Conoscenze

Python
SQL
AWS
Data pipelines
CI/CD

Strumenti

Git
Terraform
Docker

Descrizione del lavoro

We are looking for a Data Engineer who enjoys building reliable data pipelines. You will help 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 responsibilities
  • Design, 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.
  • 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 have
  • Experience with columnar databases (e.g. ClickHouse, Redshift, BigQuery).
  • Familiarity with infrastructure-as-code (e.g. Terraform).
  • Experience with Docker.
You can expect
  • Being part of a highly motivated international team.
  • High ownership and responsibility for your domain.
  • 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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