Data Engineering Consultant (Category - Architect)

Data Engineering Consultant (Category - Architect)

Sector: Oil and Gas

Location: Doha, Qatar

About Us

At Codvo, we are committed to building scalable, future-ready data platforms that power business impact. We believe in a culture of innovation, collaboration, and growth, where engineers can experiment, learn, and thrive. Join us to be part of a team that solves complex data challenges with creativity and cutting-edge technology.

Job Description:

Key Responsibilities:

Enterprise Data Architecture & Design:

Define and maintain the enterprise data architecture blueprint, including data lakes, warehouses, streaming platforms, and analytics layers.

Design logical, physical, and conceptual data models to support operational, analytical, and AI use cases.

Ensure architecture supports scalability, performance, and high availability.

Architect & Build Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems and ETL/ELT pipelines.

Integrate Diverse Data Sources: Develop processes to ingest and integrate high-volume, high-velocity data from SCADA systems, historians (like OSIsoft PI, Aspen InfoPlus.21), DCS, PLC, and IoT sensors.

Cloud Data Platform Development: Implement and manage data solutions on the Microsoft Azure cloud platform, Leveraging services like Azure IoT Hub, Azure Event Hubs, and Azure Stream Analytics for real-time ingestion and processing of operational technology (OT) data.

Data Modelling & Warehousing: Design and implement data models optimized for time-series data from industrial assets, supporting operational dashboards and real-time analytics.

Enable Advanced AI: Build the data infrastructure to support AI/ML models for predictive maintenance, operational anomaly detection, and process optimization using real-time OT data.

Required Skills and Qualifications:

10+ years of experience in data architecture, data engineering, or enterprise analytics roles.

Strong experience designing enterprise-scale data platforms in cloud and hybrid environments.

Expertise in data modelling (conceptual, logical, physical) and data integration patterns.

Deep understanding of data lakes, data warehouses, Lakehouse architectures, and real-time streaming platforms.

Hands-on experience with cloud data services (Azure preferred).

Strong knowledge of SQL, data transformation frameworks, and metadata management.

Familiarity with DevOps and DataOps practices.

Strong communication skills with the ability to engage both technical and business stakeholders.

Technical Proficiencies:

Expert-level proficiency in SQL and Python for data manipulation and pipeline development.

Big Data Technologies: Hands-on experience with distributed computing frameworks like Apache Spark (PySpark). Experience with streaming technologies like Kafka is a plus.

Cloud Platforms: Deep experience with Microsoft Azure (Azure Data Lake Storage, Azure Data Factory, Azure Databricks, Azure Synapse).

Data Warehousing/Lakehouse: Proven experience with modern data platforms Databricks Delta Lake.

AI & ML Knowledge: Understanding of machine learning lifecycles and the data requirements for training and deploying AI/ML models.

Version Control: Proficiency with Git and CI/CD best practices.

Preferred Qualifications:

Certifications such as Azure Data Engineer Expert, Azure Solutions Architect, or equivalent.

Hands-on experience with the OSDU Data Platform.

Experience in Oil & Gas, energy, or industrial data environments.

Understanding of cybersecurity considerations for OT environments and data segregation.

Experience integrating data from ERP systems like SAP.

Experience working within AI-first or analytics-driven transformation programs.

Advanced SQL skills, including query optimization and performance tuning.

Experience of constructing and maintaining enterprise knowledge graphs.

Note- Please apply via our official careers portal only, as applications sent directly to executives may not be considered.