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Information Technology 🏢 Full Time ⭐️ Verified

Data Analyst - Weekend Shift

DataDriven Solutions Inc.
Seattle, WA
Estimated Salary
USD 85.000 – USD 110.000
New
Live Update
5 Oktober 2026
Deadline
5 Okt 2027

Job Description

Join DataDriven Solutions Inc. as a Weekend Shift Data Analyst and transform raw data into actionable business intelligence. This unique full-time opportunity allows you to leverage your analytical skills during weekend hours while enjoying a competitive compensation package and collaborative environment. We're seeking a detail-oriented professional to uncover insights that drive strategic decisions for our Fortune 500 clients. If you thrive in non-traditional schedules and want to make an impact in Seattle's growing tech scene, this role is your perfect match.

Responsibilities

  • Analyze complex datasets using SQL, Python, and R to identify trends and opportunities
  • Create interactive dashboards and visualizations using Tableau and Power BI
  • Collaborate with cross-functional teams to deliver weekly performance reports
  • Develop automated data pipelines to ensure data quality and accessibility
  • Present findings to senior stakeholders through clear, compelling narratives
  • Maintain and optimize data models for weekend-specific reporting cycles
  • Support ad-hoc analysis requests with rapid turnaround solutions

Qualifications

  • Bachelor's degree in Data Science, Statistics, Computer Science, or related field
  • 3+ years of experience in data analysis with weekend shift availability
  • Advanced proficiency in SQL, Python (Pandas/Numpy), and Excel
  • Expert knowledge of data visualization tools (Tableau, Power BI, or Looker)
  • Strong statistical analysis and hypothesis testing capabilities
  • Experience with cloud platforms (AWS, Azure, or GCP)
  • Exceptional communication skills for translating technical insights
  • Portfolio demonstrating impactful data-driven projects

Required Skills

SQL Python Tableau Power BI Data Visualization Statistical Analysis AWS Excel Data Pipeline Development

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