Data Engineer

Chiesi Group•Cary, NC

2d•Hybrid

About The Position

The Data Integration Engineer will play a crucial role in designing, developing, and maintaining scalable data pipelines and cloud data architecture solutions. By leveraging on-premises and cloud technology, the Data Integration Engineer will ensure the efficient and reliable flow of data across the organization. This role is essential in enabling data-driven decision-making and supporting the company’s mission to harness the power of data for business insights and innovation. The candidate should be able to support our hybrid work model from the Cary, NC office. This position is not eligible for employment visa sponsorship. Candidates must be authorized to work in the United States without the need for sponsorship now or in the future.

Requirements

Bachelor’s degree in Computer Science, Information Technology, or a related field.
5+ years of relevant experience, with at least 3 years as a data engineer, data integration specialist, or a similar position, preferably in pharmaceuticals.
Strong proficiency in Azure SQL Database, SQL Server, Azure Data Factory, SSIS, and Databricks.
Experience with SQL and other database management systems.
Knowledge of data architecture concepts, including Master Data Management, Data Warehousing, Data Lakehouse concepts and ETL/ELT processes.
Experience working with cloud solutions.
Familiarity with other Azure services such as Azure Synapse Analytics and Azure Blob Storage.
Experience with Power BI, or other reporting solutions.
Familiarity with PowerShell, Python or other programming languages.
Familiarity with enterprise service bus (ESB) and application integration.
Ability to work effectively in a collaborative, technical local and international team environment.
Strong analytical and problem-solving skills.
Strong communication skills (written and verbal).

Responsibilities

Design, develop, and maintain reliable and scalable ETL/ELT processes, integrating structured and semi-structured data from multiple sources using Azure Data Factory, SSIS, and Databricks.
Monitor existing and new jobs and data pipelines.
Troubleshoot and resolve data-related issues in a timely manner.
Optimize data workflows for high performance and scalability.
Implement data quality checks and ensure data integrity and security across various systems.
Design and implement cloud architecture solutions to support data engineering projects.
Design and implement SSIS packages and processes to support with existing on-premise systems.
Create BI solutions like Power BI dashboards and paginated reports for business users.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
Collaborate with the IT team to offer technical solutions and resolve issues.
Maintain documentation for data processes and systems.