Responsible for maintaining knowledge of online analytical processing (OLAP) tools.
Gathers analytical requirements working with subject management experts.
Develops data frameworks for data analysis to support end-user data discovery.
Designs and develops data models that optimize analytical reporting performance.
Develops data extraction, transformation, cleansing, and loading processes between transactional and analytical systems.
Builds reports, dashboards, and OLAP databases to support end-user reporting and information requirements.
Performs statistical analyses on data and predictive forecasting.
Analyzes and interprets results using statistical techniques.
Interpret trends or patterns in complex data sets.

Basic Data Analysis: Ability to work with structured and unstructured data to identify patterns and trends.
Foundational Programming: Exposure to languages such as Python, R, or SQL for data manipulation and reporting, and clean coding practices using Git.
Introductory Machine Learning Concepts: Familiarity with basic algorithms and model-building principles.
Data Visualization: Ability to create intuitive charts, dashboards, and maps that highlight key insights and support data-driven decisions.
Understanding of Data Management: Awareness of data governance, metadata, and data quality principles.
Problem-Solving Skills: Ability to approach analytical challenges with curiosity and logical thinking.
Collaboration: Effective in cross-functional teams, balancing independent problem-solving with integration into larger, shared deliverables.
Communication: Ability to clearly and concisely present findings to diverse audiences, including fellow analysts, SMEs, and business stakeholders.
Adaptability & Learning Mindset: Eager to learn new tools, technologies, and methodologies quickly.
Domain Awareness: Interest in pattern-of-life analysis, anomaly detection, and trending models.

Junior Data Analyst – System Engineer

Key skills