> Markdown version of [/jobs/ext/4321804-data-engineer-onsite](https://www.wearedevelopers.com/jobs/ext/4321804-data-engineer-onsite). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer - ONSITE

- **Company:** The Job Network
- **Location:** Schaumburg, IL, United States
- **Experience:** Expert
- **Salary:** $100,000.0 - $130,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Java (Programming Language), Adaptable Database Systems, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Business Intelligence Development, Software as a Service, Cloud Computing, Cloud Database, Cloud Storage, Cyber Security, Information Systems, Continuous Integration, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Warehousing, JSON, Python (Programming Language), Machine Learning, Performance Tuning, Query Optimization, Software Tools, Cloud Services, Standard Sql, SAP (Applications), Software Engineering, SQL Databases, Data Streaming, Extensible Markup Language (XML), Enterprise Data Management, Data Processing, Scripting, Enterprise Software Applications, Data Ingestion, Large Language Models, Snowflake, Generative AI, Git, Data Lakes, AI Platforms, Semi-structured Data, Information Technology, Operational Systems, Machine Learning Operations, Terraform, Data Pipelines
- **Published:** October 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=271ae7d8ee6706bd

## About the Role

* Demonstrates innovation, flexibility, and self-direction, managing multiple priorities in a fast-paced environment.
 * Exceptional communication and interpersonal skills, collaboration with cross-functional team
 * Proven ability to cultivate a team-oriented environment, mentor, and engage with senior business stakeholders in business-centric dialogue.
 * Skilled in documentation for requirements, design, test, and training.
 * Experience in designing and implementing scalable data models and architecture.
 * Strong problem-solving and analytical abilities.
 * Data Validation & Quality Assurance
 * Analytical Thinking & Troubleshooting
 * Technical Documentation
 * Strong SQL development, query optimization, data transformation, and ETL/ELT pipeline development experience.
 * Experience with Snowflake, including data warehousing, data modeling, performance optimization, and cloud-based data processing.
 * Experience with cloud platforms and services such as AWS.
 * Python development and scripting experience.
 * Experience with APIs, data ingestion, integration technologies, and structured and semi-structured data, including JSON and XML.
 * Understanding of data warehouse architecture, data modeling, data validation, monitoring, troubleshooting, and performance optimization.
 * Working knowledge of Machine Learning concepts and experience preparing and transforming data to support ML models and AI/ML workloads.
 * Familiarity with AWS services such as S3, Glue, Lambda, Step Functions, and SageMaker or similar cloud technologies.
 * Experience with SAP or other enterprise ERP data is preferred.
 * Familiarity with dbt, Terraform, CI/CD, Git, Java, or similar development and deployment technologies.
 * Exposure to Generative AI, Large Language Models (LLMs), and enterprise AI platforms is a plus., * Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field (or equivalent experience)
 * Minimum of five (5) years of experience in data engineering, data integration, data warehousing, analytics engineering, or software development involving significant data responsibilities
 * Strong understanding of data architecture, enterprise systems, and business process automation.
 * Strong understanding of data governance frameworks.
 * Knowledge of information security principles and data protection best practices.
 * Demonstrated ability to lead technical initiatives while managing operational responsibilities.
 * Understanding of data processing concepts (ETL/ELT).
 * Understanding of data warehouse architecture and data modeling concepts.

## Description

* Design, develop, and maintain data pipelines that ingest data from operational systems into the enterprise data warehouse, data lake, and AI/ML environments.
 * Develop data transformation and loading processes using SQL, Python, and modern data engineering tools.
 * Integrate data from ERP platforms, SaaS applications, APIs, cloud storage, and other enterprise systems.
 * Develop and support ingestion processes using cloud services, APIs, file-based integrations, and data integration platforms.
 * Develop and perform data validation and quality checks to ensure accuracy, completeness, consistency, and reliability.
 * Identify data anomalies and assist with root-cause analysis and remediation.
 * Support the preparation, transformation, and delivery of data used by Machine Learning and AI solutions.
 * Collaborate with AI/ML engineers, developers, and business stakeholders to understand data requirements for model development and production workloads.
 * Support and maintain cloud data warehouse and data lake environments.
 * Support platform monitoring, automation, performance optimization, and production stability.
 * Document pipeline processes, data flows, architecture, integration patterns, dependencies, and support procedures