Sr. Data Analyst

4 weeks ago


Kansas City, United States Henderson Scott US Full time
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.

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