Data Engineer

Description

We are looking for a Data Engineer to help shape and scale a modern cloud-based data environment in Wood Dale, Illinois. This contract opportunity with potential for a permanent role is ideal for someone who enjoys creating reliable data solutions from the ground up and turning disconnected information into trusted reporting assets. You will work closely with business and technical partners to build a strong data foundation that improves visibility, consistency, and decision-making. The role offers a hands-on chance to define standards, streamline data delivery, and support long-term scalability in a collaborative team setting.

Responsibilities:
Create and refine scalable data models and curated datasets within BigQuery to support accurate analysis and reporting.
Build, manage, and optimize ETL workflows and data pipelines that connect information from SaaS applications and other source systems.
Develop reporting-ready data structures and dashboards that provide clear, dependable insights for business users.
Establish data quality practices, documentation standards, and performance metrics to strengthen trust in enterprise reporting.
Collaborate with cross-functional stakeholders to translate reporting objectives into well-structured data solutions.
Automate repetitive data tasks through scripting and lightweight engineering approaches using tools such as Python.
Apply governance and maintainability best practices to improve how data is organized, accessed, and supported over time.
Contribute to modernization efforts by helping move data processes away from legacy workflows into scalable cloud-based platforms.

Requirements

5+ years of experience in data engineering, analytics engineering, or a closely related discipline.
Strong practical experience with Google Cloud Platform, including deep expertise in BigQuery.
Advanced SQL skills with a proven ability to design semantic models and curated data layers.
Experience developing integrations and pipelines through APIs, ingestion frameworks, or ETL processes.
Hands-on familiarity with BI and reporting platforms such as Looker Studio, Tableau, or comparable tools.
Solid communication skills with the ability to work effectively across technical teams and business functions.
Demonstrated success in ambiguous environments where processes, models, and standards must be built from scratch.
Additional exposure to Python, Apache Spark, Apache Hadoop, Apache Kafka, Docker, or modern cloud data tooling is a plus.

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