Data Engineering Consultant (Category - Architect) at codvo-team – Maharashtra | Jobyssey

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.

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