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oracle

Senior Data Engineer

NOV
Houston, USA
Full-time
Senior · 5+ years experience
Hybrid
Discovered 2 weeks ago
PythonPySparkSQLDatabricksSparkSQL Server

Full Job Posting

Responsibilities

  • Design, develop, and optimize scalable, high-performance data pipelines supporting analytics, condition-based maintenance, and drilling optimization KPIs.
  • Build, deploy, and maintain reliable batch and streaming ETL/ELT pipelines for structured, unstructured, time-series, and high-frequency sensor data.
  • Develop data models, features, and architectures that support reporting, operational analytics, data science, machine learning, and AI applications.
  • Implement data quality controls, monitoring, testing, observability, and CI/CD practices to ensure reliable production solutions.
  • Work directly with engineers, data scientists, and operational experts to prepare data, engineer features, develop analytical solutions, and productionize predictive and machine learning models.
  • Provide technical leadership through hands-on development, establish engineering best practices, and mentor other team members.
  • Translate operational requirements into scalable data and analytical solutions while proactively identifying and addressing performance, data quality, and reliability risks.

Qualifications

  • Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science , Computer Engineering, Data Engineering, or related field.
  • Minimum 5+ years of professional experience in data engineering, software engineering, or related data-focused roles.
  • Strong hands-on experience with Python, PySpark , SQL and modern data engineering technologies.
  • Proven experience designing and operating scalable batch and streaming data pipelines.
  • Strong knowledge of data modeling, ETL/ELT, distributed processing, and cloud/hybrid data architectures.
  • Experience with platforms and technologies such as Databricks, Spark, SQL Server, Data Lakes, and SQL/NoSQL databases.
  • Experience with software engineering practices including Git, automated testing, CI/CD, and deployment automation.
  • Demonstrated technical leadership and ability to collaborate across engineering, data science, and operational teams.
  • Preferred Qualifications
  • Experience with data science, machine learning, or AI, including developing or productionizing analytical and predictive models.
  • Experience with predictive maintenance, anomaly detection, equipment monitoring, or operational optimization.
  • Experience with industrial IoT, telemetry, SCADA, WITSML, or other operational technology data.
  • Knowledge of drilling operations, drilling optimization KPIs, condition-based maintenance, and equipment reliability.
  • Databricks or cloud data engineering certification.
  • Experience with AWS or other major cloud platforms.
  • Knowledge of oil and gas industry operations and technology

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