Developer III - Database

Cencora•Conshohocken, PA

1d•Remote

About The Position

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today! IntrinsiQ Specialty Solutions, Inc. - Work with business analysts and business users to gather and interpret business requirements for multiple financial and healthcare systems including large data warehouses. Design and develop database applications using SQL Server Integration Services, TSQL, and Stored Procedures. Consult with the business to determine the logical design for new business solutions according to existing data architecture. Perform code reviews, analyze execution plans, and re-factor inefficient code. Follow data standards, resolve data issues, complete unit testing, and complete system documentation for ETL processes. Collaborate with business analysts, source system experts, and other team members to determine data extraction and transformation requirements. Design, develop, test, deploy, and maintain data processing systems and build scalable data pipelines using Azure Data Factory to extract, transform, and load structured as well as unstructured data. Implement secure storage and access controls for sensitive data using Azure Key Vaults. Leverage Azure Databricks for advanced analytics tasks including ETL jobs and machine learning workflows. Utilize Spark fundamentals to optimize the performance of big data processing tasks. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Ensure data quality by implementing appropriate validation checks and error-handling mechanisms. Work closely with DevOps teams to integrate data engineering processes into CI/CD pipelines. Monitor the performance of data pipelines and troubleshooting any issues that arise. Document technical specifications, processes, and best practices. Utilize Azure Databricks, Azure DW, Python and Scripts.

Requirements

Requires a Bachelor’s degree or foreign equivalent in Computer Science, Computer Engineering, Information Technology or a related field.
Requires minimum 2 years of experience in a Data Engineer, Software Engineer or related position maintaining data processing systems and building scalable data pipelines using Azure Data Factory.
writing complex SQL queries to perform data extraction
troubleshooting issues in production in a timely fashion and working across teams of different skill levels
configuring and supporting managing ETL automation with SQL Server Integration Services
developing Spark applications for data extraction, transformation, and aggregation
utilizing Azure Functions, Azure Databricks, Azure DW, Python and Scripts.
Experience developing Spark applications for data extraction, transformation, and aggregation.
Experience in technologies relevant to data/information management, such as SQL, RDBMS, Data Lake/Hadoop, MDM, Metadata, and Data Quality; working with clinical data.

Responsibilities

Work with business analysts and business users to gather and interpret business requirements for multiple financial and healthcare systems including large data warehouses.
Design and develop database applications using SQL Server Integration Services, TSQL, and Stored Procedures.
Consult with the business to determine the logical design for new business solutions according to existing data architecture.
Perform code reviews, analyze execution plans, and re-factor inefficient code.
Follow data standards, resolve data issues, complete unit testing, and complete system documentation for ETL processes.
Collaborate with business analysts, source system experts, and other team members to determine data extraction and transformation requirements.
Design, develop, test, deploy, and maintain data processing systems and build scalable data pipelines using Azure Data Factory to extract, transform, and load structured as well as unstructured data.
Implement secure storage and access controls for sensitive data using Azure Key Vaults.
Leverage Azure Databricks for advanced analytics tasks including ETL jobs and machine learning workflows.
Utilize Spark fundamentals to optimize the performance of big data processing tasks.
Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Ensure data quality by implementing appropriate validation checks and error-handling mechanisms.
Work closely with DevOps teams to integrate data engineering processes into CI/CD pipelines.
Monitor the performance of data pipelines and troubleshooting any issues that arise.
Document technical specifications, processes, and best practices.
Utilize Azure Databricks, Azure DW, Python and Scripts.