Our client represents the connected world, offering innovative and customer-centric information technology experiences, enabling Enterprises, Associates, and Society to Rise™.

They are a USD 6 billion company with 163,000+ professionals across 90 countries, helping 1279 global customers, including Fortune 500 companies. They focus on leveraging next-generation technologies, including 5G, Blockchain, Metaverse, Quantum Computing, Cybersecurity, Artificial Intelligence, and more, on enabling end-to-end digital transformation for global customers.

Our client is one of the fastest-growing brands and among the top 7 IT service providers globally. Our client has consistently emerged as a leader in sustainability and is recognized amongst the ‘2021 Global 100 Most sustainable corporations in the World by Corporate Knights.

We are currently searching for a Data Engineer:

Responsibilities:

• Develop and maintain data pipelines for batch and streaming data ingestion and processing.
• Design and implement robust data models and architectures that meet business requirements.
• Utilize Azure cloud-based data platforms, including Databricks and Delta Live Tables, for data engineering tasks.
• Ensure data quality through profiling, validation, and root cause analysis, maintaining accuracy, completeness, and consistency.
• Apply workflow orchestration tools to automate data pipeline execution and manage dependencies.
• Implement CI/CD practices for automated testing and deployment of data pipelines.
• Integrate monitoring and alerting mechanisms to track pipeline health and proactively address performance issues.
• Follow Agile development methodologies, actively participating in sprint activities and adapting to project requirements.

Requirements:

• Proficiency in Python and PySpark with knowledge of software engineering best practices.
• Expertise in Azure cloud services for data storage, compute, and security.
• Experience with data pipeline design and automation.
• Strong skills in data quality management and root cause analysis.
• Familiarity with workflow orchestration tools.
• Knowledge of CI/CD practices for data engineering workflows.
• Ability to monitor, troubleshoot, and optimize data pipelines.
• Strong understanding of Agile principles and collaboration in iterative environments.

Languages

• Advanced Oral English.
• Native Spanish.

Note:

• Fully remote

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