MUSE GROUP

Muse Group empowers music makers. We create the world’s most popular apps for playing, recording, and composing music.

Through our innovative learning tools, expansive music catalogs, and free open-source software, we make it easier for millions — from beginners to experienced musicians — to be creative every day.

Our talented team of music lovers collaborates all over the globe, from Limassol to Seoul, Boston to Berlin. We’re an ambitious company with the drive and culture of a startup — with many more exciting Muse Group developments to come.

As we continue to grow, we're looking for a talented Analytics Engineer to join the Core analytics team As the Analytics Engineer, you will act as the bridge between raw data management and actionable business insights, ensuring that data is accurate, accessible, and primed for analysis.

Responsibilities:

1. Data Integration and Pipeline Development.

2. Tool and Technology Standardization.

3. Data Quality Assurance:

• Implement systems and checks to monitor data accuracy, consistency, and completeness.
• Identify, rectify, and prevent data quality issues, ensuring data integrity across the analytics landscape.

4. Data Governance and Compliance:

• Develop and maintain a data governance framework that outlines how data is acquired, stored, processed, and shared.
• Ensure data management practices are in compliance with internal policies and external regulations.

5. Collaboration and Cross-Functional Support.

6. Database Management and Optimization:

• Oversee the architecture and performance of databases used for analytics.
• Optimize queries, indexes, and data storage for efficient retrieval and analysis.

7. Documentation and Knowledge Sharing.

8. Performance Monitoring and Scalability:

• Monitor the performance of data pipelines and databases, ensuring they meet the required service level agreements (SLAs).
• Plan and implement solutions for scaling the analytics infrastructure in line with the organization's growth.

9. Data Security and Privacy.

Required Experience and skills:

• Good knowledge of SQL.
• Visualisation tools experience: Redash/Superset/Tableau/Power BI/Google Data Studio.
• Good knowledge of probability theory and statistics.
• Understanding of A/B testing principals and theory.
• Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations.
• Demonstrated experience with one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people/ML.
• 4+ years in the Data space as an analyst, engineer, or equivalent.
• 4+ years experience designing, implementing, operating, and extending commercial Kimball or other enterprise dimensional models.
• 4+ years working with a large-scale (1B+ Rows) Data Warehouse, preferably in a cloud environment.
• 2+ years experience building reports and dashboards in a data visualization tool.
• 1+ years creating project plans to identify tasks, milestones, and deliverables.