Senior Analytics Engineer (m/f/d) at ICE Services

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

26 Jun, 26

Salary

0.0

Posted On

28 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Modeling, Snowflake, ETL/ELT, Data Ingestion, Data Transformation, BI Tools, Dashboarding, Data Quality, Python, AWS, Docker, GitHub, Agile Methodologies, Dimensional Modeling, Star Schemas

Industry

Musicians

Description

About ICE ICE is a music technology company built by rightsholders, for rightsholders. We simplify the complexities of the music royalty chain through an innovative suite of licensing, processing, and copyright services, enabling our customers to accurately and efficiently compensate songwriters and composers for the use of their works. Serving over 330,000 rightsholders and leveraging a copyright database comprising 55 million musical works, ICE’s operations touch 250+ territories to distribute more than €1bn in royalties per year, with a total of over €5bn distributed to date. About the Role We are looking for an experienced Senior Analytics Engineer to join our cross-functional product engineering team. In this role, as part of a modern, product-centric technology organization working with agile methodologies, you will play a key role in shaping and building analytics capabilities that turn complex music usage and copyright data into meaningful and reliable insights. By driving the design and evolution of high-quality data models, enabling reliable business metrics, and delivering trusted data insights, you will help music societies and publishers better understand their data and accurately compensate songwriters and composers when their music is used around the world. While the primary focus of the role is analytics engineering, this position also offers exposure to data engineering, including working with ETL/ELT pipelines, data ingestion to ensure reliable and scalable data flows that support analytics and reporting needs. Key Responsibilities: Partner with stakeholders to translate complex business questions into scalable data models and analytics products, owning the delivery and quality of those products within a cross-functional team. Design and deliver impactful dashboards and reporting solutions providing clear insights for business stakeholders. Design scalable analytics data models and transformation pipelines, and define reusable datasets, business metrics, and semantic layer components used for reporting and analysis. Collaborate with platform and data engineers to design, improve, and scale ETL/ELT pipelines. Continuously optimize data workflows and transformations for performance, scalability, and cost efficiency. Ensure high standards of data quality and reliability across analytics datasets, pipelines, and reporting layers by implementing validation checks and monitoring. Ensure documentation, lineage, and dataset definitions are complete and consistently maintained across analytics assets. Contribute to the design and improvements of analytics platform architecture by proposing different approaches to the use of warehouses, reporting tools, and analytics services within the team. Mentor and support business users in effectively leveraging data visualization and analytics tools. Requirements and Qualifications: Required Strong SQL expertise and extensive experience designing scalable data models in modern data warehouses. Deep understanding of data modeling principles, including dimensional modeling and star schemas. Proven hands-on experience working with Snowflake data warehouse. Strong understanding of ETL/ELT architecture and data ingestion pipelines. Experience building data transformation pipelines within a modern data platform. Experience building dashboards and reports in BI tools. Proven experience building business-facing dashboards and reporting solutions. Strong analytical and problem-solving skills. Familiarity with AWS cloud platform. Experience with Python or other scripting languages for data processing or automation. Experience working with containerized environments (e.g., Docker) to support development and deployment of data pipelines and services. Ability to write clean, maintainable, and modular code. Experience using GitHub in collaborative development environments. Nice to Have Experience with AWS QuickSight / Quick Suite. Experience implementing data quality monitoring and validation frameworks. Hands-on experience building data ingestion pipelines. Exposure to AI-enabled analytics solutions, such as systems that allow users to query data using natural language. What we offer: Competitive local benefits based on your location We promote flexible working regarding time and/or place Both mental and physical health initiatives Corporate pension scheme Comprehensive training and development opportunities Industry insider events, team socials and company events Enhanced holiday allowance We welcome candidates from all backgrounds, regardless of age, disability, gender, gender identity, gender expression, race, religion or belief, sexual orientation, socioeconomic background, and any other protected characteristic. We are committed to making all stages of our recruitment process accessible to candidates with disabilities. Please speak to our recruitment team and we will work with you to make reasonable adjustments to ensure you can perform at your best throughout your application.

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Responsibilities

The Senior Analytics Engineer will partner with stakeholders to translate complex business questions into scalable data models and analytics products, owning their delivery and quality. Key tasks include designing impactful dashboards, scalable analytics data models, and transformation pipelines to deliver trusted data insights.