Data Engineer - Apache Airflow - Remote.

détails du poste

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détails du poste

Here at Randstad Digital, we are looking for a data engineer with experience of deploying Apache Airflow and pushing data through a complex environment including Snowflake

Key Responsibilities:

Design, deploy and maintain the data ingestion and pipeline orchestration system using Apache Airflow.

Develop and maintain connectors to integrate various in-house solutions, including APIs, file-based systems, and SQL databases.

Oversee containerized environments using Docker or Podman, with an emphasis on security, speed, and robustness.

Implement and manage efficient data transformations using Python-based tools.

Ensure reliability and performance by debugging and optimizing complex systems.

 

Essential Skills:

Apache Airflow: Extensive experience with data processing orchestrators, with a focus on Apache Airflow.

Containers: Proficiency in container management (Docker, Podman), with experience in Kubernetes or OpenShift as a plus.

Python: Strong coding abilities, particularly in Python, and experience with data processing libraries like pandas, polars, duckdb, and great-expectations.

Linux Environment: Experience managing Linux server environments (RHEL experience is a plus).

Snowflake (Preferred): Hands-on experience with Snowflake or similar SQL-based databases.

Data Warehousing & Data Architecture: Strong understanding of data architecture, data warehousing, and modern data formats such as Parquet, Avro, and Arrow.

 

Preferred Qualifications:

Experience in software engineering, with at least 2 years focused on data processing.

Familiarity with HPC/parallel processing.

Experience with TDD (Test-Driven Development) and DQC (Data Quality Checks).

Previous work experience in a scientific IT environment is a plus.

  

Skills & Attributes:

Ability to work independently on assigned tasks, while collaborating effectively on system design.

Strong problem-solving skills with a willingness to debug and optimize complex systems.

Documentation is key — proactive in creating and maintaining documentation as an off-line communication tool.

Here at Randstad Digital, we are looking for a data engineer with experience of deploying Apache Airflow and pushing data through a complex environment including Snowflake

Key Responsibilities:

Design, deploy and maintain the data ingestion and pipeline orchestration system using Apache Airflow.

Develop and maintain connectors to integrate various in-house solutions, including APIs, file-based systems, and SQL databases.

Oversee containerized environments using Docker or Podman, with an emphasis on security, speed, and robustness.

Implement and manage efficient data transformations using Python-based tools.

Ensure reliability and performance by debugging and optimizing complex systems.

 

Essential Skills:

Apache Airflow: Extensive experience with data processing orchestrators, with a focus on Apache Airflow.

Containers: Proficiency in container management (Docker, Podman), with experience in Kubernetes or OpenShift as a plus.

Python: Strong coding abilities, particularly in Python, and experience with data processing libraries like pandas, polars, duckdb, and great-expectations.

Linux Environment: Experience managing Linux server environments (RHEL experience is a plus).

Snowflake (Preferred): Hands-on experience with Snowflake or similar SQL-based databases.

Data Warehousing & Data Architecture: Strong understanding of data architecture, data warehousing, and modern data formats such as Parquet, Avro, and Arrow.

 

Preferred Qualifications:

Experience in software engineering, with at least 2 years focused on data processing.

Familiarity with HPC/parallel processing.

Experience with TDD (Test-Driven Development) and DQC (Data Quality Checks).

Previous work experience in a scientific IT environment is a plus.

  

Skills & Attributes:

Ability to work independently on assigned tasks, while collaborating effectively on system design.

Strong problem-solving skills with a willingness to debug and optimize complex systems.

Documentation is key — proactive in creating and maintaining documentation as an off-line communication tool.

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Jeremy Knight

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