Data Quality Development Analyst at Eram Talent

Dammam, Eastern Province, Saudi Arabia -

Full Time

Start Date

Immediate

Expiry Date

30 May, 26

Salary

0.0

Posted On

01 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Quality Assurance, Data Quality Solution Development, Metadata Repository, Master Data Management, Business Intelligence Tools, Data Quality Procedures, Data Policy Definition, Data Profiling, SQL, Tableau, Power BI, Analytical Skills, Problem-Solving, Communication Skills, Data Accuracy, Process Improvement

Industry

Oil and Gas

Description

Eram Talent is in search of a dedicated Data Quality Development Analyst to enhance our commitment to delivering exceptional staffing solutions. In this pivotal role, you will ensure that our data quality standards are met and continuously developed, contributing to our data-driven decision-making capabilities across the organization. The role holder is responsible for designing data quality assurance policies and standards, developing an enterprise data quality solution, defining metadata repositories and master data management to enable leverage enterprise data for business intelligence. The role holder is also responsible for installing and maintaining business intelligence tools and fine-tuning their performance. Key Responsibilities Responsible for designing, testing, deploying and documenting the data quality procedures and their outputs Design processes and technology to enable the client to leverage the enterprise data for business intelligence purposes. Define the data policy, standards and guidelines and ensure consistency. Coordinate with Master Data Quality Manager and define metadata repository for digitally and physically storing and cataloguing data. Design master data management to provide processes, governance, policies, standards and tools to define and manage master data. Define quality assurance policies and standards to ensure consistency in business intelligence reports. Identify and highlight issues related to data quality in order to improve accuracy of reports leading to proper decision making. Liaise with Master Data Quality Manager to provide support in development, operations and maintenance of dashboards and reports in the Technology environment. Install business intelligence tools and configures hardware and software components. Perform users’ administrator setup and provides continuous support for maintenance. Perform business intelligence performance tuning to ensure optimal performance. Recommend training and development interventions for team members to build their capabilities. Contribute to the identification of opportunities for the continuous improvement of systems, processes and practices to increase productivity and operational efficiency. Implement all relevant Department’s policies, processes, procedures and instructions so that work is carried out in a controlled and consistent manner. Contribute to the preparation of timely and accurate reports to meet departmental requirements, policies and standards. Bachelor’s degree in information technology, or equivalent from a recognized and accredited university is required. 5+ years of experience in data analysis, data quality, or a similar role. Knowledge of Data Quality principles, policies and procedures. Knowledge of Data Quality tools. Strong understanding of data governance, data quality metrics, and data management principles. Experience with data profiling tools and techniques. Proficiency in SQL and experience with data visualization tools (e.g., Tableau, Power BI). Strong analytical and problem-solving skills. Excellent communication skills and ability to work collaboratively with diverse teams. Detail-oriented with a strong focus on data accuracy and reliability.

Responsibilities

The analyst will be responsible for designing, testing, deploying, and documenting data quality procedures and developing an enterprise data quality solution. This includes defining data policies, standards, and metadata repositories to enable leveraging enterprise data for business intelligence purposes.