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Qualifications

Required Qualifications

1. Education

• Bachelor’s degree in Analytics, Information Systems, Computer Science, Statistics, Mathematics, Business, or a related field.
• Equivalent combination of education and relevant experience may be considered.

2. Experience

• 0–2 years of experience in analytics, business intelligence, reporting, data analysis, or a related field.
• Internship, co-op, or project-based experience in data analysis, dashboard development, or reporting is acceptable.

3. Technical Skills

• Proficiency in SQL, including joins, aggregations, subqueries, and query optimization.
• Working knowledge of Python for data analysis and automation.
• Experience with Python libraries such as pandas, numpy, matplotlib, and seaborn.
• Experience developing dashboards and reports in Power BI and/or Tableau.
• Strong proficiency in Microsoft Excel, including formulas, pivot tables, lookups, charts, and data analysis functions.
• Experience using Power Query for data extraction and transformation.
• Familiarity with cloud data warehouse platforms such as Snowflake.
• Exposure to Azure and AWS environments.
• Foundational understanding of data modeling and data relationships.

Preferred Qualifications

• Experience with DAX or other reporting calculation languages.
• Familiarity with BI reporting best practices and visualization standards.
• Exposure to data governance, reporting documentation, and quality control processes.
• Understanding of end-to-end reporting lifecycle processes.
• Experience in a large, matrixed, or enterprise environment is a plus.
• Core Competencies
• Professional Competencies
• Strong analytical and problem-solving skills.
• High attention to detail and commitment to data accuracy.
• Effective written and verbal communication skills.
• Strong organizational and time management abilities.
• Ability to work independently and collaboratively in a team environment.
• Adaptability and willingness to learn new tools and business processes.

Key Responsibilities

1. Analytics and Reporting

• Develop, maintain, and enhance recurring and ad hoc reports, dashboards, and visualizations to support business operations and performance management.
• Analyze large and structured datasets to identify trends, anomalies, and business opportunities.
• Translate business requirements into accurate, scalable, and user-friendly reporting solutions.
• Perform data validation, reconciliation, and quality checks to ensure reporting integrity and consistency.
• Prepare and present analytical findings in a clear and professional manner.

2. SQL Development and Performance Tuning

• Write, test, and optimize SQL queries for data extraction, transformation, and reporting.
• Improve query performance by applying efficient logic, join strategies, aggregation methods, and filtering techniques.
• Troubleshoot and resolve query-related issues affecting reporting accuracy or performance.
• Work with relational database structures and cloud-based warehouse tables, including Snowflake.
• Support reusable query development and reporting logic standardization.

3. Python Analytics Workflows

• Use Python to support data preparation, automation, transformation, validation, and analytical tasks.
• Assist in automating repetitive reporting and analysis processes where appropriate.
• Document scripts, logic, assumptions, and analytical methods to support maintainability and consistency.