Senior Dredging Data Engineer

About the role

NMDC Dredging and Marine is looking for a Senior Dredging Data Engineer in Abu Dhabi. The role leads the management and optimisation of on-premises server-based data infrastructure focused on dredging data, designs and maintains data pipelines, and provides technical leadership within the DevOps team.

Key responsibilities

• Manage and optimise the on-premises server-based data infrastructure for dredging data.
• Design, implement and maintain data pipelines, solving complex data engineering problems.
• Provide technical leadership to junior and senior DevOps team members, building scalable, high-performance data solutions.
• Work with the DevOps team and end-users to understand data requirements from business and project needs.
• Build scalable ETL pipelines for efficient data extraction, transformation and loading, integrating data across systems.
• Oversee data storage and retrieval to ensure data integrity, performance and availability.
• Perform advanced data analysis and build reporting solutions to support decisions and operations.
• Lead testing and validation to ensure data quality and resolve data issues.
• Keep up with industry trends, adopt emerging technologies, and mentor other data engineers.

Required profile

• Bachelor's degree in Computer Science, Software Engineering or equivalent.
• At least 7 years of experience in data engineering or related roles, with a proven track record of designing and implementing data solutions.
• Experience with on-premises servers and/or cloud platforms (Azure, AWS, Google Cloud).
• Knowledge of RESTful APIs and integration with front-end services.
• Experience supporting back-end development and delivering data solutions for desktop and/or web applications.
• Contribution to open-source projects or a strong GitHub profile.
• Familiarity with data science projects and methodologies.
• Exposure to dredging and/or civil engineering.

Required skills

• Python and/or Scala
• SQL and NoSQL
• Version control (GIT)
• Data science familiarity