Data Engineer IV 4P/792

Key Responsibilities: Design, develop, and maintain ETL and ELT data pipelines. Build integrations using RESTful APIs, microservices, and event-driven architectures. Develop cloud-based data solutions using Azure, AWS, or Google Cloud Platform. Integrate data across ERP, CRM, LIMS, ITSM, collaboration platforms, and custom applications. Develop reusable data services, APIs, integration components, and automation solutions. Write and optimize Python and SQL code for data processing and transformation. Support modern data architectures, cloud platforms, and enterprise integration patterns. Apply data governance, security, authentication, and access-control standards. Troubleshoot data quality, performance, integration, and production issues. Collaborate with application teams, architects, data engineers, security teams, and business stakeholders. Create technical documentation, data mappings, interface specifications, and operational procedures.

Required Qualifications: 5+ years of experience in data engineering, software engineering, or systems integration. Strong experience developing ETL/ELT pipelines. Proficiency in Python and SQL.Experience designing and consuming RESTful APIs. Experience with event-driven integrations, microservices, and integration tools. Knowledge of Azure, AWS, or Google Cloud Platform. Experience integrating enterprise applications and data systems. Understanding of data governance, cybersecurity, authentication, and access control. Strong analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications: Experience with AI/ML platforms, agent frameworks, vector databases, and retrieval-based architectures. Experience with Databricks, data lakes, lakehouse platforms, or cloud data warehouses. Familiarity with CI/CD, containers, orchestration, and DevOps practices. Utility, energy, or regulated-industry experience is preferred.