Data Engineer

Intrado is dedicated to saving lives and protecting communities, helping them prepare for, respond to, and recover from critical events. They are seeking a Data Engineer to build robust data pipelines for internal business analytics, ensuring raw data is ingested, cleaned, and ready for analysis.

Responsibilities:

• Build and maintain Azure Data Factory pipelines to ingest data from multiple sources
• Write the Python code in Databricks to clean raw data and move it into the silver layer, handling deduplication, type casting, and validation
• Monitor daily jobs and troubleshoot failures. You are the first line of defense in ensuring that pipelines are stable and do not break
• Implement automated checks to verify that data arriving in the lake matches the source systems

Requirements:

• 5+ years of experience in Data Engineering, specifically focused on building and maintaining ETL/ELT pipelines of large-scale operational and financial data in a cloud environment
• Proficiency in building and optimizing data pipelines using Azure Data Factory and Databricks or comparable modern data orchestration and distributed processing frameworks
• Strong proficiency in SQL for data analysis and Python for scripting and transformation
• Experience implementing automated data quality checks (e.g., schema validation, null checks). A proactive approach to identifying pipeline failures and implementing fixes to prevent recurrence
• Experience working with data schemas and APIs from common enterprise platforms like Microsoft Dynamics 365 F&O, Salesforce, ServiceNow
• Demonstrated experience using LLMs to streamline data engineering workflows and improve development efficiency
• Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a closely related technical field
• Prior experience working in a technology company or SaaS environment