Main Responsibilities:
- Design and implement data visualizations to assist the organization with both internal and external data needs.
- Analyze and report on critical aspects such as pricing, product strategies, finance, and marketing initiatives.
- Diagnose and resolve technical issues promptly, ensuring smooth operations.
- Collaborate with the product owner, development team, and data analytics specialists to refine requirements and devise solutions.
- Partner with fellow software engineers and team members to navigate a variety of technical challenges.
- Develop and execute intricate SQL queries and Python scripts to tackle diverse business issues.
- Conduct ongoing data quality assessments to ensure the reliability and integrity of data across multiple platforms.
- Mentor junior analysts and team members, encouraging a supportive and collaborative learning atmosphere.
Essential Qualifications:
- A bachelor's degree or equivalent experience in a relevant field.
- A minimum of 5 years in a role such as Data Analyst, Business Intelligence Analyst, or similar.
- Solid experience with visualization tools like PowerBI, Tableau, or Qlik.
- Strong grasp of SQL and relational database systems (e.g., SQL Server).
- Practical knowledge of Python for data analysis, scripting, and automation purposes.
- Capable of working both independently and collaboratively within a team.
- Experience leading or acting as a subject matter expert on small to medium-scale projects.
- A keen interest in continuous learning and professional growth.
Preferred Qualifications:
- Experience with ETL tools (e.g., Azure Data Factory, Talend, etc.).
- Familiarity with big data technologies and cloud platforms, especially Azure.
- A portfolio showcasing visualizations developed in Tableau, Power BI, or similar applications.
- Understanding of deployment automation, continuous integration/continuous delivery (CI/CD), and Infrastructure as Code (IaC).
- Knowledge of data security protocols, compliance requirements, and encryption techniques.
- Familiarity with machine learning methodologies and applications.
- Ability to engage effectively with cross-disciplinary teams.
