Data Engineer
Summary
Designs and maintains ETL pipelines, integrates ERP and business data, and builds scalable workflows to deliver reliable datasets for analytics and reporting.
**This is a direct hire, hybrid role for our client located in the Iowa City-Cedar Rapids metro. Eligible candidates are required in office for standing meetings each week. Candidates must be eligible to work in the United States without visa or sponsorship.**
Our client is seeking a Data Engineer to design, develop, and maintain the data infrastructure that supports reporting, analytics, and business decision-making across the organization. This role will build scalable data pipelines, improve data quality, and deliver reliable datasets that enable operational and strategic insights. Working closely with technical and business teams, the Data Engineer will transform complex data into actionable information that drives business performance. The ideal candidate is a problem-solver who enjoys working with large datasets, designing efficient data workflows, and continuously improving data reliability and performance.
Responsibilities
Design, develop, and maintain ETL/ELT pipelines supporting enterprise reporting and analytics.
Integrate data from ERP, manufacturing, and business systems into centralized data platforms.
Build and manage scalable data workflows across extraction, transformation, and loading processes.
Develop and maintain data models, testing frameworks, and technical documentation.
Monitor pipeline performance and troubleshoot data quality, schema, and workflow issues.
Collaborate with business stakeholders to understand data requirements and deliver scalable solutions.
Automate manual processes and improve data delivery efficiency.
Ensure data accuracy, consistency, security, and reliability across systems.
Stay current with emerging data engineering technologies and best practices.
Qualifications
Strong experience building and supporting production data pipelines.
Proficiency in SQL and Python.
Experience working with structured, semi-structured, and unstructured data.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and organizational skills.
Ability to manage multiple priorities in a fast-paced environment.
Nice to Haves
Experience in manufacturing, ERP, or operational data environments.
Experience with workflow orchestration tools such as Prefect or Apache Airflow.
Experience with CDC or incremental data processing strategies.
Familiarity with dbt, MongoDB, Redis, Microsoft SQL Server, and Docker.
Knowledge of modern data architecture and cloud analytics platforms.
Our Vetting Process
At Emergent Staffing, we work hard to find the data engineers who are the right fit for our clients. Here are the steps of our vetting process for this position:
Application (5 minutes)
Online Assessment (40 minutes)
Initial Video Interview (30-45 minutes)
Client Phone Interview (30 minutes)
Client On-site interview (60 minutes)
Job Offer!
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