Data Engineering Analyst - Build Scalable Azure Pipelines

Metyis
Valladolid, Spain
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours

Tech stack

Information Engineering Python (Programming Language) Machine Learning SQL Databases Azure Data Factory Data Lakes Data Analytics Data Pipelines Atlassian Bamboo

Job description

Metyis is seeking a Data Engineering Analyst with 1+ year of experience to join our international Data and Analytics team, based in Barcelona. You will build and optimize data pipelines, work with Azure Data Factory and Data Lake Storage, and partner with data scientists to enable analytics and machine learning.You should have a solid foundation in SQL and Python, and be comfortable collaborating across multilingual teams.#J-*****-Ljbffr

Requirements

Metyis is seeking a Data Engineering Analyst with 1+ year of experience to join our international Data and Analytics team, based in Barcelona. You will build and optimize data pipelines, work with Azure Data Factory and Data Lake Storage, and partner with data scientists to enable analytics and machine learning. You should have a solid foundation in SQL and Python, and be comfortable collaborating across multilingual teams. #J-*****-Ljbffr

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:24 min

The governance failures of centralized data lakes

Mario Meir-Huber · LIVE

1:14 min

Evolution of distributed SQL database architectures

Wei Hu Wei Hu · World Congress 2024

1:32 min

Structuring platforms for new services and data analytics

Nevelina Aleksandrova · LIVE

6:08 min

Applying software engineering environments and testing to data pipelines

Matthias Niehoff Matthias Niehoff · World Congress 2024

6:24 min

Distributed data lakes and containerized computing clusters

Ulrich Wurstbauer +1 · LIVE

6:23 min

Visualizing data pipelines using Azure Machine Learning Designer

Jose Luis Latorre Millas · LIVE

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