Data Engineer

DivIHN Integration • Chicago, IL

10d

About The Position

The Data Engineer will support and modernize the client’s data architecture as part of an effort to establish a modern data estate. This high-growth, high-visibility opportunity involves building data pipelines that support daily operations, reporting, and decision-making. The role will help migrate legacy processes to a cloud-native platform built on Azure and Databricks, and contribute to shaping the target-state architecture.

The engineer will develop and maintain ETL pipelines, evolve cloud-based data infrastructure, and build governed data products for reporting, analytics, automation, and emerging AI use cases. The role also involves applying security-by-design principles and working with data owners and stewards to establish quality, classification, lineage, access-control, and governance standards. Candidates must be eligible to work on a W-2 basis; third-party and C2C candidates are not considered.

Requirements

• 2–5 years of experience designing, developing, and deploying data pipelines and modern cloud data solutions.
• Strong proficiency in Python programming and PySpark.
• Hands-on experience with Databricks, including notebooks, jobs, Delta Lake, and Unity Catalog.
• Experience building and operating orchestration pipelines with Azure Data Factory (ADF).
• DevOps experience, including Git-based workflows and CI/CD.
• Self-starter with strong ownership and problem-solving skills, able to manage multiple priorities in a fast-moving environment.
• Strong communication and collaboration skills, including the ability to translate business requirements into practical data solutions and work effectively with technical and non-technical stakeholders.
• Must be eligible to work on a W-2 basis; third-party and C2C candidates are not considered.

Nice To Haves

• Experience working with Salesforce data.
• SQL experience, including complex queries, tuning, and data modeling.
• Experience working in an Azure environment.

Responsibilities

• Own technical solutions that evolve data architecture and integration patterns while addressing changing business needs.
• Develop and maintain ETL pipelines that transform raw data into usable formats for analysis, reporting, and a centralized data repository.
• Evolve data pipeline infrastructure using cloud-native tools such as Azure Data Factory and Databricks, or similar toolsets.
• Collaborate with data stewards, product teams, and business stakeholders to ensure data is accurate, reliable, and consistent.
• Participate in an agile team, own testing through test automation, drive DevOps capabilities, and use infrastructure-as-code practices to enable repeatable, controlled deployments across environments.
• Build trusted, well-governed data products that support reporting, analytics, automation, and emerging AI use cases.
• Apply security-by-design principles, including least-privilege access, secrets management, encryption, data classification, and appropriate protection of sensitive data.
• Partner with data owners and stewards to implement data quality, classification, lineage, access controls, and governance standards across the data platform.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed