Summary
Tarshid is seeking a Data Analyst Lead in Riyadh to help its business units make data-driven decisions. The role includes gathering and validating data, preparing recurring and ad-hoc reports, building dashboards, and identifying trends, anomalies, and risks. The successful candidate will support Tarshid’s Data Lake and Business Intelligence implementation, including data requirements, migration testing, data quality, and automated reporting. The role will also contribute to predictive analytics and AI/ML use cases.
The posting
As published on tarshid.com.sa. Pulled from the employer's site and shown as they wrote it.
Job Description – Data Analyst Job Summary
The Data Analyst will play a critical role in enabling Tarshid’s business units to make data-driven decisions. In the short term, this role will focus on collecting, cleaning, consolidating, and analyzing data from multiple systems to provide reliable reporting and insights. In the medium to long term, the Data Analyst will actively contribute to the design, testing, and adoption of Tarshid’s Data Lake and Business Intelligence platforms, enabling advanced analytics and AI-driven insights across the organization.
Key Responsibilities Immediate (Pre–Data Lake)
- Gather, validate, and consolidate data from multiple siloed systems and manual sources.
- Develop recurring and ad-hoc reports for Finance, Strategy, Shared Services, and Operations.
- Build dashboards and visualizations (Excel, Power BI) to track KPIs such as project progress, financial performance, and energy savings.
- Highlight trends, anomalies, and risks to support timely decision-making.
Transition (During Data Lake Implementation)
- Support IT/Digital Transformation in defining data requirements, integration points, and reporting needs.
- Map existing manual reports to future automated dashboards.
- Identify data gaps, inconsistencies, and recommend data quality rules.
- Participate in testing and validation of migrated datasets and dashboards.
Future (Post–Data Lake)
- Leverage centralized data to deliver predictive and prescriptive analytics.
- Enable AI/ML use cases (e.g., IoT smart meters, energy savings forecasting, operational optimization).
- Create scalable, automated dashboards for business self-service reporting.
- Partner with business stakeholders to translate strategic questions into data-driven insights.
Key Performance Indicators (KPIs)
- Deliver recurring standard reports within agreed timelines (e.g., weekly, monthly).
- Respond to ad-hoc data requests within 2–3 business days, depending on complexity.
- Ensure accuracy levels of at least 95% in reports and dashboards delivered.
- Support incident resolution related to reporting/data accuracy within 1 business day.
- Participate in governance meetings and provide updates as per the DT/IT governance cadence.