Your Tasks

1. Data Collection: Gather, clean, and preprocess data from various sources, using Python, SQL, or other relevant languages, to ensure data quality and accuracy.

2. Data Analysis: Conduct exploratory data analysis (EDA) to identify patterns, trends, and insights within datasets, employing strong mathematical and statistical knowledge.

3. Data Visualization: Create clear and informative data visualizations using tools like Power BI, including proficiency in reporting and dashboarding.

4. Data Modeling: Build and maintain data models, especially Star architecture, and apply them to data analysis.

5. ETL and ELT: Develop ETL and ELT pipelines for data processing, transformation, and loading.

6. Big Data: Work with big data sets, demonstrating experience in handling and analyzing large volumes of data.

7. API Integration: Retrieve and store data through REST APIs and access various types of databases, both relational and non-relational.

8. Advanced Analytics: Utilize advanced analytics tools, including M-Language (Power Query) and DAX, for in-depth data analysis.

9. Process Automation: Apply an in-depth understanding of process automation to streamline data-related workflows.

10. Agile Principles: Work in alignment with Scrum and Agile principles, contributing to agile development methodologies.

11. Software Development: Experience in the software development lifecycle is a plus, demonstrating the ability to collaborate on software projects.

Required Skills and Qualifications for Junior Data Analysts:

• Programming Languages: Proficiency in one or more of the following languages: Python, SQL, JavaScript, CSS, HTML, with the ability to write code for data analysis and manipulation.

• Data Warehousing: Familiarity with data modeling, especially Star architecture, for effective data storage and retrieval.

• Power BI: Proficiency in Power BI for reporting and dashboard creation, including experience with the Power BI Cloud service environment.

• Process Automation: In-depth understanding of process automation to improve data-related workflows.

• Big Data: Experience in handling and analyzing big data sets efficiently.

• API Integration: Experience with REST APIs for retrieving and storing data, including accessing various database types.

• Advanced Analytics: Advanced knowledge of M-Language (Power Query) and DAX for in-depth data analysis.

• Agile Methodologies: Strong understanding of Scrum and Agile principles, contributing to agile development methodologies.

• Software Development Lifecycle: Experience in the software development lifecycle is a plus, showcasing the ability to collaborate on software projects.

• Microsoft Environment: Proficiency in Microsoft tools and platforms, including SharePoint, Teams, PowerApps, Power Automate, and Azure.

• Team Collaboration: Experience working effectively in a team and contributing to collaborative data projects.

• Creativity: Ability to tell stories with data and a „can-do attitude“ to find innovative solutions.

• Certifications: Possession of one or more Agile certifications (e.g., Scrum Developer CSD, Scrum Master CSM) and/or data-related certifications (e.g., MS SharePoint, MS Dynamics 365 Developer Associate, MS Power BI Data Analyst Associate, Microsoft 365 Certified, Data Analyst certification) is a plus.