Primary purpose of job

The Senior Data Analyst is responsible for data engineering, designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis. Plays a crucial role in building and managing the data pipelines that enable efficient and reliable data integration, transformation, and delivery for all data users across QatarEnergy.

Accountability:

Technical role responsible for operating and ingesting data into QatarEnergy data repositories (e.g. Digital Data Platform, Data warehouse …etc) to ensure the availability of data for data visualization, data analytics and digital use cases by designing, building and reviewing data integration pipelines.

Maintain close alignment with the data governance, data architecture, data security and overall business strategy. Continuous collaboration with the various QatarEnergy business entities to ensure the data governance practices are applied on the data repositories (e.g. Data Quality).

Experience & Skills

• 8 years’ experience within Oil and Gas, understanding of Upstream and Downstream Data requirements.
• 5 Years of proven experience in data management disciplines, including data integration, modelling, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks within Oil and Gas
• Expert knowledge in Apache technologies such as Kafka, Airflow, and Spark to build scalable and efficient data pipelines.
• Full understanding of Data Discovery, Data Visualization, Data Warehousing, Data Governance (e.g., datalogging, profiling, ownership/stewardship, Data Quality. etc)
• Strong experience in database technologies and techniques SQL, NoSQL
• A must have strong hands-on experience designing, developing, deploying, testing and maintaining data services on MS Azure, (ADLS, Azure Synapse, Azure SQL, Azure Databricks. etc)
• Able to make quick decisions and solve technical problems to provide an efficient environment for project implementation. Able to make quick decisions and solve technical problems to provide an efficient environment for project implementation.
• Awareness of data integration patterns, data modelling and data architecture
• Strong ability in programming languages such as Java, Python, or C/C++
• Ability in data science languages/tools such as SQL, R, SAS, or Excel
• Strong knowledge in ETLs, APIs, algorithms, data structures and business intelligence tools (Power BI)
• Ability to regularly learn and adopt new technology.
• Ability to debug and fix data issue.
• Ability to communicate across all levels of the organization and work with diverse project teams.
• Good Knowledge of Applications Architecture and Information Security Principles

Education

A bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field; master’s degree preferred.