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 and 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.

We are seeking an Analytics Engineer to join our team and play a pivotal role in shaping our analytics infrastructure and processes. You will act as a bridge between raw data management and actionable business insights, ensuring that data is accurate, accessible, and primed for analysis.

Key responsibilities:

Data Integration and Pipeline Development:

• Develop and maintain robust, scalable data pipelines to integrate data from various sources.
• Ensure timely, accurate data ingestion and processing, making data available for analytics and operational uses.

Tool and Technology Standardization:

• Evaluate and recommend analytics tools and platforms that best fit the organization's needs.
• Establish a standardized toolkit across analytics teams, ensuring compatibility and interoperability.

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.

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.

Collaboration and Cross-Functional Support:

• Work closely with data scientists, analysts, and business stakeholders to understand and fulfill their data needs.
• Offer technical support for analytics initiatives, including experiment setups, data extraction, and performance monitoring.

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.

Documentation and Knowledge Sharing:

• Document data pipelines, architectures, and governance policies for transparency and easy reference.
• Train and guide analytics teams on best practices, tools, and methodologies.

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.

Data Security and Privacy:

• Implement and monitor security measures to protect sensitive data and prevent unauthorized access.
• Ensure adherence to data privacy regulations and best practices, especially concerning personally identifiable information (PII).

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Required experience:

• Good knowledge and proven experience of practice SQL
• Good visualisation tools experience. Understanding of their work and what gaps they solved.
  - Redash/Superset/Tableau/Power BI/Google Data Studio.

• Python experience or Scala
• Good knowledge of probability theory and statistics. You should thinks in hypotheses and understands the essence of analytical work.
• 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/science
• 3+ years in the Data space as an analyst, engineer, or equivalent
• 3+ years experience designing, implementing, operating, and extending commercial Kimball or other enterprise dimensional models
• 3+ 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

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