Data Integration Engineer

GEOLOG is a world leader in geosciences and drilling data management. We specialize in managing large datasets from drilling rigs, fluid samples analyses and cuttings digital repositories in the oil and gas industry. Our mission is to drive innovation and efficiency through data-driven decision-making.
The Company seeking a highly skilled and experienced Data Integration Engineer or Architect to join our team.
THE POSITION
This role involves designing, implementing, and managing complex data pipelines and data lakehouse architectures. The ideal candidate will bring a deep understanding of data engineering, big data technologies, and machine learning operations (MLOps).
Responsibilities include, but are not limited, to:

• Design and develop scalable data pipelines for processing and storing vast volumes of data from drilling rigs and digital repositories.
• Implement reliable data pipelines to integrate disparate data sources into a unified Data Lakehouse.
• Develop data quality pipelines to ensure accuracy and build trusted datasets.
• Design a Data Lakehouse solution that accurately reflects business operations.
• Assist with data platform performance tuning, including partitioning and compaction of physical data models.
• Ensure data quality and integrity throughout the data lifecycle.
• Collaborate with various teams to meet data requirements and deliver effective data solutions.
• Optimize data retrieval and create dashboards for data visualization and analysis.
• Provide guidance in data visualizations and reporting efforts, ensuring alignment with business objectives.
• Stay updated with emerging technologies and trends in data infrastructure.
• Implement best practices for data security and compliance.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
• Minimum of 3 years of experience in Data Engineering or a similar role.
• Proficiency in big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure).
• Strong programming skills in Python, Scala, or Java.
• Experience with SQL and NoSQL databases.
• Familiarity with data pipeline tools such as Apache Airflow or Dagster.

• Strong problem-solving and analytical capabilities.
• Effective communication and team collaboration skills.
• Adaptability in a dynamic and fast-paced environment.
• Knowledge of the oil and gas industry is beneficial.
• Expertise in Python libraries (PySpark, Pandas, NumPy, Scikit-Learn).
• Proficiency in CI/CD principles, ETL processes, and Git.