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# Data Engineer & Insights Analyst

- **Company:** THE PHOENIX
- **Location:** Harrisburg, PA, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Big Data, Cloud Computing, Cloud Database, Data Validation, Data Conversion, Data Files, Data Governance, Data Systems, Relational Databases, Machine Learning, Meta-Data Management, Systems Development Life Cycle, SQL Databases, Unstructured Data, Enterprise Data Management, Data Logging, Sql Optimization, Electronic Medical Records, AWS Lambda, Data Lineage, Data Management, Data Pipelines
- **Published:** November 6, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-insights-analyst-harrisburg-pa--7de60725-b0c7-456f-ac22-4fd4be08a50c

## About the Role

Analysis Skills, Data Management, Cloud Computing, Scalable System Development, Electronic Medical Records, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), AWS Lambda, Apache, Data Sets, * Advanced SQL skills and experience with relational databases.

 * Strong experience building and optimizing large-scale data pipelines and architectures.
 * Experience developing dashboards, reports, analytical models, and decision-support products.
 * Experience working with student-level higher education data and linking education data with employment and wage data.
 * Strong analytical and problem-solving skills, including root-cause analysis.
 * Experience processing large, complex, disconnected, and unstructured datasets.
 * Strong project management and organizational skills.
 * Experience working with cross-functional teams in a dynamic environment.

## Description

* Design, build, and maintain scalable data pipelines and cloud-based data architectures.
 * Develop data solutions using AWS services, including S3, Glue, Redshift, EMR, Athena, Kinesis, and Lambda.
 * Build and manage data orchestration workflows using Apache Airflow, AWS Step Functions, or similar tools.
 * Extract, transform, and integrate large datasets from multiple sources using SQL and big data technologies.
 * Develop analytical data environments supporting statistical analysis, predictive modeling, and machine learning.
 * Perform data quality checks, validation, monitoring, logging, and root-cause analysis.
 * Develop dashboards, reports, analytical models, and decision-support products.
 * Support data conversion and system modernization initiatives.
 * Implement data governance, metadata management, data lineage, privacy, and security controls.
 * Collaborate with cross-functional teams to support enterprise data and analytics initiatives.