Position: Power BI Engineer
Company: DataArt
Category: Data Engineer
Experience required: 3y
English level: upper
Published: 2022-10-01T00:00:00+03:00

**Project overview:**

We are developing a digital health application for the German market for patients with muscular diseases. The project started this year and we are working on delivering the first increment by the end of the year.

We are developing the backend and 2 native mobile applications - iOS and Android. For now, we are developing a new analytics module to grab data to make insights based on that and we are looking for a Power BI data engineer to visualize the data and further - to support the solution, and do the data analysis.

The project team consist of around 20 members, containing business analyst, designer, and testers. 

**This project can offer you:**

— work in a friendly environment,
— best engineering practices in terms of development,
— a boost of knowledge in healthcare and data protection,
— better understanding of the specifics of developing the application in a regulated environment.

**TECHNOLOGY STACK**

BI tools (Power BI, Looker, Qlik, Tableau, Sisense, Microstrategy), SQL, ELT/ETL

**Responsibilities:**

— Collect and maintain the set of business reporting requirements
— Working/building dashboards and BI reports using based on the above requirements
— Set up and maintain BI tools, infrastructure, and integration with company data sources
— Propose data schema and data flow optimization for reporting performance and enhancement as needed
— Data visualization
— Help with the deployment and support of newly introduced features
— Work with the QA team, bug fixing

**Requirements:**

— 3-5 years of experience or 3-5 completed projects
— Knowledge of data cleansing, preparation, exploration, manipulation, and visualization as well as such data management areas as data modeling, data quality, and data warehouse.
— SQL (DML part)
— BI tools (Power BI, Looker, Qlik, Tableau, Sisense, Microstrategy, etc)
— Awareness of data analysis theory and statistics
— Awareness of other data management fundamentals (ELT/ETL, metadata management, data warehouse/lakes patterns, distributed systems)
— Spoken English