(IL-111) - Principal Data Operations Engineer

(IL-111) - Principal Data Operations Engineer

07 feb
|
Epicor
|
Monterrey

07 feb

Epicor

Monterrey

.We're on the lookout for a skilled Cloud Data Engineer to help shape our data platform, enabling seamless integration, storage, and analysis of vast datasets.
In this role, you'll work with industry-leading tools and collaborate with cross-functional teams to deliver scalable, secure, and high-performance data solutions.
If you thrive on tackling complex challenges and have a knack for optimizing cloud-based architectures, we want to hear from you!
**What you will be doing**:- Perform all duties and maintain all standards in accordance with company policies, procedures, and internal controls such as SOX.- Design, implement, and maintain cloud-based data pipelines to enable efficient storage, processing,



and analysis of large volumes of data.- Collaborate with data engineers, and other stakeholders to understand requirements and translate them into scalable and reliable data platform architectures.- Evaluate and select appropriate cloud infrastructure and services to support data storage, processing, and analytics needs, considering factors such as scalability, performance, extendibility, cost, and security.- Implement data ingestion pipelines, integrating various, disparate data sources and ensuring data quality, integrity, and timeliness.- Design and optimize data storage solutions, including data lakes, data warehouses, and data marts, to support different types of data processing and analysis.- Implement data processing and transformation workflows using technologies such as Azure Spark, Azure SQL Pools / data warehouses or other cloud-native data processing services.- Develop and maintain data governance and security policies, ensuring compliance with data protection regulations and industry best practices.




**What you will bring**:- Azure Data Engineering Fundamentals certification or relevant experience- Proficiency in data processing frameworks such as Azure Spark, or cloud-native data processing services (Azure Data Lake, Azure Synapse, Azure SQL Pools and On-Demand Clusters, Azure Data Factory, Azure Databricks)- Experience with data integration and ETL (Extract, Transform, Load) processes and best practices, including tools like cloud-native orchestration services experience with workload and job optimization for cost reduction.- Understanding of distributed computing principles and scalable architectures.- Excellent problem-solving and troubleshooting skills, with the ability to address complex data platform challenges.- Strong communication and collaboration skills to work effectively with cross-functional teams- Deep knowledge of data ingestion strategies and understanding of the Data Lake and Dimensional data models within Azure

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