Data Engineer

We are looking for a Data Engineer to support scalable data solutions for a long-term contract opportunity in The Woodlands, Texas. This role focuses on designing and optimizing data pipelines, integrating large-scale data sources, and enabling reliable access to critical business information. The ideal candidate will bring strong hands-on experience with modern big data technologies and a practical approach to building efficient ETL workflows.

Responsibilities:
• Build, maintain, and enhance robust data pipelines to process large volumes of structured and unstructured information.
• Develop ETL workflows that transform raw data into reliable datasets for analytics, reporting, and operational use.
• Use Python and Apache Spark to engineer high-performance data processing solutions across distributed environments.
• Work with Apache Hadoop ecosystems to manage storage and support scalable data operations.
• Integrate streaming and event-driven data using Apache Kafka to improve data availability and timeliness.
• Monitor data workflows, troubleshoot processing issues, and implement improvements that increase reliability and efficiency.
• Collaborate with technical and business stakeholders to understand data needs and translate them into practical engineering solutions.
• Document pipeline architecture, data flow logic, and operational procedures to support maintainability and team knowledge sharing.

Qualifications:

• Proven experience working as a Data Engineer in environments that handle large and complex datasets.
• Strong hands-on expertise with Python for data engineering, automation, and pipeline development.
• Practical experience using Apache Spark for distributed data processing and transformation.
• Familiarity with Apache Hadoop and related big data frameworks.
• Experience with Apache Kafka for data streaming or message-based integration.
• Solid understanding of ETL design, data transformation practices, and data quality principles.
• Ability to diagnose technical issues, optimize data workflows, and deliver dependable solutions in a collaborative setting.

Compensation

Based on experience

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