Job Title: Data Management Senior Specialist
Experience: Minimum 7+ Years
Location: Oman
Work Mode: On-Site
Employment Type: Full-Time

JOB BRIEF

One of our esteemed clients is seeking a Data Management Senior Specialist to oversee and maintain data management technologies that support operations and data quality. This role ensures seamless data integration, master data management, and data warehouse environments while maintaining agreed service levels.

QUALIFICATIONS

• Bachelors degree in Computer Science or related field.
• 7+ years of experience in data management and information systems.
• Strong knowledge of E&P processes, data management, and SQL Server 2019.
• Hands-on experience in SSIS administration, Data Warehouse, and Data Lake environments.
• Proficiency in Linux administration, SQL scripting, PySpark, and Kafka administration.
• Strong problem-solving and organizational skills.

Administration Activities:

• Manage daily administration of data management technologies like SSIS, MDS, MDM, Kafka, Python, and Data Lake.
• Oversee data management application upgrades, infrastructure changes, and data migrations.
• Plan and execute installation, configuration, deployment, and integration activities.
• Maintain, patch, and upgrade data management applications.
• Monitor and ensure optimal performance of data management applications.
• Ensure adherence to SLAs, KPIs, ITIL processes, and compliance requirements.
• Build and maintain strong relationships with business teams and IT service providers.
• Document application functionalities, processes, and maintenance procedures.

ETL & Data Integration:

• Develop ETL/replication solutions using Microsoft SQL Server Integration Service (SSIS), Kafka, and PySpark.
• Support and maintain data integration pipelines for periodic and real-time data loads.
• Optimize data processing performance to support near real-time operations.
• Gather business requirements and implement data validation rules.
• Assist data warehouse end-users in understanding and querying data.

Enterprise Data Quality:

• Conduct data quality profiling using SSIS, Kafka, PySpark, and Information Quality Metrics.
• Implement data quality rules for standardization and cleansing.
• Generate data quality reports and support testing processes.