Epicor

Senior Data Operations Developer

Epicor

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $60,000 - $170,000 per year

Job Level

Senior

Tech Stack

AzureCloudERPETLMySQLPostgresPythonSparkSQLSSISTableau

About the role

  • 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.
  • 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.

Requirements

  • Strong experience in Microsoft Azure – minimum 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 processes and best practices, including tools like cloud-native orchestration services experience with workload and job optimization for cost reduction.
  • Familiarity with data governance, data security, and compliance frameworks.
  • 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. (ex: delta lakes and medallion architecture)
  • Comfortable with Microsoft SQL data technologies (SSAS/SSIS/SSRS) or relevant AzureSQL, MySQL, Postgres experience