Data Engineer

Description

We are looking for a Data Engineer to help shape and strengthen the organization's data ecosystem in Spartanburg, South Carolina. This role focuses on building scalable data structures and reliable integration solutions that support analytics, operational reporting, and long-term business goals. The ideal candidate brings a strong background in modern data platforms and enjoys partnering with technical and business teams to deliver secure, high-quality data solutions.

Responsibilities:
Develop and refine data models, storage frameworks, and analytical repositories that enable efficient access to trusted information.
Create scalable architecture approaches that support enterprise objectives while improving performance, reliability, and long-term maintainability.
Establish data design standards, architectural patterns, and governance practices that promote consistency, quality, and security across platforms.
Partner with software developers, analytics teams, and business stakeholders to translate operational needs into practical data solutions.
Build and enhance data pipelines and integration processes that move information accurately across systems and support reporting and analysis.
Implement processes for master data, metadata, and data quality management to strengthen governance and regulatory compliance.
Assess emerging tools, cloud technologies, and platform options to recommend solutions that balance cost, scalability, and functionality.
Work closely with data engineering peers to encourage strong technical alignment, knowledge sharing, and continuous improvement across the team.

Requirements

5+ years of experience in data architecture, database design, and enterprise data management environments.
Hands-on expertise with data modeling, data warehousing concepts, and ingestion or ETL frameworks.
Proficiency with technologies such as Python, Apache Spark, Apache Hadoop, Apache Kafka, and related big data tools.
Experience working with NoSQL platforms, middleware technologies, and cloud-based data environments such as Snowflake.
Demonstrated success designing resilient, high-performing data solutions for complex organizational settings.
Strong communication and collaboration skills, with the ability to work effectively across technical and leadership teams.
Knowledge of data governance, data quality practices, and compliance-focused design principles.
Certifications in cloud or solution architecture are valued.

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