Data Engineer

Required Skills & Experience

• 5–7 years of Data Engineering experience, including strong experience designing and developing cloud-based data solutions.
• Experience with Azure data services such as Azure Databricks, Azure Data Factory, ADLS Gen2, Synapse Analytics, and/or Microsoft Fabric.
• Hands-on proficiency with Python, SQL, PySpark, and Apache Spark.
• Strong understanding of ETL/ELT, data modeling, distributed computing, and lakehouse architectures.
• Experience working with SQL and NoSQL data stores.
• Experience building and supporting production-grade data pipelines, including testing, monitoring, error handling, and operational support.
• Working knowledge of Git, CI/CD, and cloud DevOps practices.
• Strong analytical, troubleshooting, communication, and cross-functional collaboration skills, with the ability to operate independently and navigate ambiguity.

Nice to Have Skills & Experience

• Local to the Dallas-Fort Worth, TX area.
• Ability to read and understand Java code.
• Experience developing solutions involving Generative AI, RAG, agentic AI, and/or enterprise search.
• Familiarity with LLM concepts including embeddings, vector search, prompt engineering, grounding, evaluation, and model inference.
• Familiarity with Kafka, Azure Event Hubs, or other streaming technologies.
• Experience with Docker, Kubernetes/AKS, APIs, and microservices.
• Experience implementing data governance, metadata management, data lineage, and access controls.
• Relevant Microsoft Azure certifications are a plus.

Job Description

Insight Global is seeking a Data Engineer to support a large healthcare client within its Pharmacy Benefit Management (PBM) business. This individual will support an application called AIM (Accuracy Improvement and Monitoring), which analyzes and compares forecasted revenue from client contract guarantees against actual revenue.

The role is part of a broader Connected PBM Ecosystem initiative focused on establishing a more unified, consistent source of data across information systems. The team is currently focused on expanding the AIM application to support additional clients and identifying opportunities to integrate AIM with other systems and applications.

The environment is also undergoing targeted modernization. AIM sits downstream from a parent application that is being modernized, so this individual will need to work effectively within an evolving technical environment and understand dependencies across systems.

Longer term, the AIM roadmap includes agentic AI development and AI-enabled capabilities. While deep AI/ML engineering experience is not required, familiarity with concepts such as RAG, vector databases, Generative AI, and LLMs will be valuable as the application evolves.

Day-to-day responsibilities include:

• Execute user stories and develop data engineering solutions using Claude Code and other AI-assisted development tools.
• Design, develop, test, and support solutions using Python, PySpark, SQL, Apache Spark, and Azure data services.
• Work within an application ecosystem where AIM's parent system is Java-based and undergoing modernization, requiring the ability to understand upstream changes and their downstream impacts.
• Build and maintain reliable, production-grade data pipelines while supporting testing, monitoring, troubleshooting, and operational needs.
• Collaborate with technical and business stakeholders to understand requirements, troubleshoot issues, and translate business needs into technical solutions.
• Operate independently, navigate ambiguity, solve problems, communicate confidently with stakeholders, and execute technical solutions with minimal oversight.