Data Architect

Data Architect (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.

Our Vision: Engineering the Future of Energy with Data

Our digital transformation is moving from strategy to execution. We have a clear roadmap of high-impact data and AI use cases designed to fundamentally re-engineer our operations—from improving efficiency and implementing predictive maintenance on critical assets to enhancing subsurface modeling for better exploration outcomes. This is not just an IT upgrade; it is a core business imperative to create a more resilient, efficient, and intelligent energy company. We are now building the core team of innovators and builders to deliver these initiatives. This role is critical to bringing that vision to life, moving beyond theory to engineer the specific, robust data solutions that will power our most strategic projects and deliver measurable value.

The Opportunity:

The Data Architect will be responsible for designing, governing, and evolving the organization's enterprise data architecture, ensuring that data platforms are scalable, secure, interoperable, and AI-ready. This role focuses on defining data models, integration patterns, governance standards, and architecture blueprints that enable analytics, AI, and digital products at scale.

The architect will work closely with data engineers, solution architects, cloud teams, business stakeholders, and cybersecurity teams to ensure data architecture aligns with business priorities and regulatory requirements.

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.

Cloud Data Platforms & Integration:

• Architect cloud-native data platforms using Azure (ADF, Synapse, Databricks, Fabric) and/or GCP equivalents.
• Design secure hybrid architectures integrating on-premises systems with cloud data platforms.

Data Governance, Quality & Security:

• Define and enforce data governance frameworks, including metadata management, data lineage, data ownership, and stewardship models.
• Establish data quality standards, validation rules, and monitoring mechanisms.
• Ensure compliance with ISO 27001, NIA Qatar, data privacy, and internal cybersecurity policies.
• Define data security architecture including encryption, access control, and role-based data access.

Analytics, AI & Advanced Use Cases:

• Design data architectures that support advanced analytics, AI/ML, and digital twin initiatives.
• Collaborate with data scientists and analysts to optimize data models for analytics and AI consumption.

Architecture Governance & Leadership:

• Establish data architecture standards, reference architectures, and best practices.
• Review solution designs to ensure alignment with enterprise data architecture principles.

Required Skills and Qualifications:

• Bachelor's or master's degree in computer science, Data Engineering, Information Systems, or related field.
• 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.
• Orchestration: Experience with workflow orchestration tools like Airflow, Dagster, or Azure Data Factory.
• Databases: Strong understanding of both relational (e.g., PostgreSQL, SQL Server) and NoSQL databases. Experience with graph databases (e.g., Neo4j) and vector databases is highly desirable.
• 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.
• Knowledge of containerization technologies (Docker, Kubernetes).
• Experience of constructing and maintaining enterprise knowledge graphs.