Azure Data Engineer

RADcube•Carmel, IN

About The Position

Key Responsibilities Assist in the development, testing, and maintenance of ETL processes and data pipelines. Support data ingestion and transformation from multiple source systems into target databases. Perform data quality checks, validation, and reconciliation to ensure accuracy and completeness. Document transformation logic, data mappings, and source-to-target specifications. Collaborate with BI teams to support upstream data fixes and resolve data discrepancies. Assist in User Acceptance Testing (UAT) and support defect identification and remediation. Contribute to the continuous improvement of ETL workflows and data governance practices. Participate in data warehouse modernization initiatives using cloud platforms such as AWS and Azure, including migration and optimization of legacy workflows. Engage in client-facing communication to gather requirements, provide updates, and deliver technical solutions aligned with business needs. SQL & T-SQL Development Responsibilities Interpret business and technical requirements to write and optimize SQL and T-SQL transformations. Develop and maintain strong stored procedures to support efficient data processing and business logic. Support the documentation of SQL logic in Technical Requirements Documents (TRDs) and mapping specifications. Validate SQL outputs against source data to ensure alignment with business rules. Troubleshoot and resolve data discrepancies at the SQL and T-SQL level under the guidance of senior developers. Assist with UAT defect fixes by adjusting SQL logic and retesting outputs.

Requirements

Hands-on experience with SQL and T-SQL development in a professional setting.
Ability to write and understand SELECT, INSERT, and UPDATE statements.
Proficient in joins, aggregations, subqueries, filtering logic, and stored procedure development.
Strong troubleshooting skills to identify and resolve data issues at the query level.
Experience working with cloud-based data platforms (AWS, Azure) is a plus.
Education: Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field. Relevant certifications or coursework are a plus.
Experience: 4–8 years in Data Engineering, ETL, or analytics support roles; hands-on SQL and T-SQL development experience is required.
Understanding of data engineering concepts and data pipeline architecture
Strong analytical thinking, problem-solving ability, attention to detail, and excellent written/verbal communication.
Must be a great team player with proven ability to collaborate effectively across teams and engage in client-facing communication to understand requirements and present solutions.
Adaptability in a Fast-Paced Environment
Ability to Work Independently with Limited Instruction

Nice To Haves

Prior experience in healthcare, insurance, or claims data environments is strongly preferred.
Exposure to ETL tools such as SSIS, Azure Data Factory (ADF), or similar platforms.
Familiarity with cloud-based data warehouse modernization (AWS, Azure) is highly desirable.
Exposure to reporting tools such as Power BI, Tableau, or Cognos is a plus.

Responsibilities

Assist in the development, testing, and maintenance of ETL processes and data pipelines.
Support data ingestion and transformation from multiple source systems into target databases.
Perform data quality checks, validation, and reconciliation to ensure accuracy and completeness.
Document transformation logic, data mappings, and source-to-target specifications.
Collaborate with BI teams to support upstream data fixes and resolve data discrepancies.
Assist in User Acceptance Testing (UAT) and support defect identification and remediation.
Contribute to the continuous improvement of ETL workflows and data governance practices.
Participate in data warehouse modernization initiatives using cloud platforms such as AWS and Azure, including migration and optimization of legacy workflows.
Engage in client-facing communication to gather requirements, provide updates, and deliver technical solutions aligned with business needs.
Interpret business and technical requirements to write and optimize SQL and T-SQL transformations.
Develop and maintain strong stored procedures to support efficient data processing and business logic.
Support the documentation of SQL logic in Technical Requirements Documents (TRDs) and mapping specifications.
Validate SQL outputs against source data to ensure alignment with business rules.
Troubleshoot and resolve data discrepancies at the SQL and T-SQL level under the guidance of senior developers.
Assist with UAT defect fixes by adjusting SQL logic and retesting outputs.