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# Analytics Engineer

- **Company:** JustDice GmbH
- **Location:** Hamburg, Germany (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Business Analytics Applications, Data Analysis, Data Architecture, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Visualization, Python (Programming Language), Standard Sql, SQL Databases, Tableau (Software), Gitlab, Git, Data Analytics, Software Version Control, Data Pipelines
- **Published:** August 10, 2026
- **Apply:** https://www.adzuna.de/details/5834774983

## About the Role

* Bachelor's degree in STEM fields or previous experience in related jobs or projects.

 * Minimum 3 years of experience in data science, engineering, analytics, or a related field.

 * Strong SQL, Python programming skills.
 * Knowledge of dbt
 * Proficient in data modeling, data architecture, and data engineering principles.
 * Knowledge of GitLab or similar git-based version control systems.
 * Ability to validate hypotheses through data visualization.
 * Strong analytical skills.

 * Autonomy and ability to work independently.
 * Strong problem-solving skills.
 * Growth mindset and eagerness to learn new technologies and methodologies.
 * Is able to communicate in a pragmatic and professional manner.

## Description

The Analytics Engineer occupies an essential role within our data-driven organization, collaborating with product, tech, and marketing teams while reporting to the Business Intelligence Lead. The primary purpose of this role is to support stakeholders in making informed decisions by proactively identifying challenges and opportunities through data analysis, leading to tangible and positive impacts on the business.

What you'll do?

 1. Data Engineering
 1. Design, construct, and enhance data pipelines utilizing SQL, Python, dbt, git, and AWS services.
 2. Create and maintain data architecture and data models for various business domains.
 3. Implement data quality and validation processes to guarantee data accuracy and consistency.
 4. Automate and streamline data integration, ETL, and ELT processes to improve efficiency.
Analytics

 1. Establish and implement data requirements and analytics solutions with our tech and product teams.
 2. Plan, execute, and evaluate experiments with our marketing and product teams.
 3. Establish the KPIs and metrics that will be used by the business.
Develop appropriate monitoring tools for these indicators.

 4. Convey the message using visualization tools (Tableau)


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