Senior Data Engineer

CBTS serves enterprise and midmarket clients in all industries across the United States and Canada. CBTS combines deep technical expertise with a full suite of flexible technology solutions- - including Application Modernization, Managed Hybrid Cloud, Cybersecurity, Unified Communications, and Infrastructure solutions. From developing and deploying modern applications and the secure, scalable platforms on which they run, to managing, monitoring, and optimizing their operations, CBTS delivers comprehensive technology solutions for its clients transformative business initiatives. For more information, please visit www. cbts. com .

www. onx. com

The Big Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and infrastructure to process and analyze massive datasets. This role supports data- driven decision- making by ensuring data is clean, accessible, and optimized for analytics and machine learning applications.

• Data Architecture & Engineering:

• • Design and implement big data solutions using Hadoop, Spark, and other distributed systems
    
  • Develop, construct, test, and maintain scalable data architectures and processing systems
    
  • Integrate data from various sources into centralized data lakes or warehouses.

• ETL & Data Pipeline Development:

• • Build robust ETL pipelines for batch and real- time data ingestion
    
  • Optimize data flow and processing for performance and scalability.

• Collaboration & Integration:

• • Work closely with data scientists, analysts, and business stakeholders to translate requirements into technical solutions
    
  • Collaborate with architects to ensure systems align with enterprise architecture.

• Monitoring & Maintenance:

• • Monitor data systems for performance, reliability, and security.
  • Troubleshoot and resolve data- related issues.

• Governance & Compliance:

• • Implement data governance, privacy, and security protocols.
  • Ensure compliance with regulatory standards.

• Proficiency in big data technologies: Hadoop, Spark, Hive, Pig, Impala
• Experience with NoSQL databases: MongoDB, Cassandra, HBase.
• Strong programming skills: Python, Java, Scala, or Shell scripting.
• Familiarity with data modeling, warehousing, and MPP platforms.
• Knowledge of cloud platforms (AWS, Azure, GCP) and data services.
• Experience with tools like Kafka, Flume, Airflow, and data visualization platforms.

• Bachelor s or master s degree in computer science, Engineering, or related field.
• 2 5+ years of experience in data engineering or big data roles.
• Certifications in Big Data technologies or cloud platforms are a plus.

• Strong analytical and problem- solving abilities.
• Excellent communication and collaboration skills.
• Ability to manage multiple priorities and work independently.

Work Environment: Hybrid