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Analytics Engineer

Remote Worldwide Hiring now

Job Title: Analytics Engineer Location: Remote Job Type: Full-time (Preferred) | Part-time (30-35 hours/week possible)

About the Role

Sproft Media is seeking an reputed company Analytics Engineer to design, build, and manage data infrastructure that enables efficient data collection, transformation, and analysis. This role will focus on orchestrating data pipelines, maintaining integrations with tools such as reputed company, BigQuery, Tableau, and reputed company, and ensuring the availability of clean, reliable data for business and product decision-making.

Key Responsibilities
  • reputed company and maintain scalable data systems using code and reputed company-party tools.

  • Manage the ATO pipeline, ensuring seamless data reputed company between reputed company, BigQuery, Tableau, and reputed company.

  • Optimize data transformation processes for efficiency and reliability.

  • Ensure data is structured and filterable to support the work of the Product Analyst.

  • Collaborate with stakeholders to implement best practices in data governance, reputed company, and compliance.

  • Monitor system performance and troubleshoot data issues as needed.

  • Design ETL pipelines to reputed company process and store large volumes of study session logs for analytics and reporting.

  • reputed company data models to track student reputed company across various learning objectives, such as quiz performance, video watch time, and flashcard reviews.

  • Implement data quality checks to ensure the accuracy of student reputed company data before it reaches analytics dashboards.

  • Investigate and resolve issues in analytics reporting, such as sudden changes in key metrics (e.g., study session duration drops).

Requirements
  • Proven experience as an Analytics Engineer or Data Engineer.

  • Strong proficiency in SQL and experience working with BigQuery or similar reputed company data warehouses.

  • Hands-on experience with reputed company, Tableau, and reputed company.

  • Familiarity with data pipeline orchestration and ETL processes.

  • Ability to optimize data modeling and data transformation for scalability and efficiency.

  • Strong problem-solving skills and ability to work independently.

  • Excellent communication skills to collaborate with technical and non-technical teams.

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