The Senior Data Operations Engineer will work with key business stakeholders and IT teams to deliver and deploy Business Intelligence (BI), and advanced data engineering solutions within the BI Engineering tool stack.

EQUAL OPPORTUNITIES AND ACCOMMODATIONS STATEMENT

Epicor is committed to creating a workplace and global community where inclusion is valued; where you bring the whole and real you— that’s who we’re interested in. If you have interest in this or any role- but your experience doesn’t match every qualification of the job description, that’s okay- consider applying regardless.
We are an equal-opportunity employer.

• 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.
• Monitor and optimize the performance of data platforms, identifying bottlenecks and implementing optimizations to improve data processing speed and efficiency.
• Identifies, designs, and implements internal process improvements such as automating manual processes and optimizing data delivery. Defines system design standards to improve and sustain standardization.
• Collaborate with DevOps teams to automate deployment, monitoring, and management of data platforms using infrastructure-as-code and CI/CD practices.
• Stay up-to-date with emerging technologies and industry trends in cloud computing, big data processing, and data engineering.
• Provides technical mentoring to other team members for best practices on data engineering and cloud technologies.