Position: Senior Data Engineer for AI-Driven Productivity Platform
Company: SSA Group
Experience required: 5y
English level: upper

Join SSA Group team working on an AI-powered productivity platform that enhances work efficiency and empowers employees, teams, and executives with real-time productivity awareness and actionable recommendations to unleash the potential for optimization and growth.

**PROJECT**
The project’s core is the cutting-edge AI that provides the world’s first standardized productivity score, determines optimal work patterns, identifies which actions most positively impact team productivity growth, and makes personalized, prioritized AI-driven recommendations.

The project caught the attention of Forbes and has been recognized as a Sample Vendor in the Gartner Report.

**TECHNOLOGY STACK**
+ Python, Pandas, NumPy
+ AWS: S3, Data Pipelines, Athena
+ Apache SuperSet

**TEAM**
CTO, AI team of 2 Data Scientists, Data Engineer and Fullstack Developer

**CANDIDATE REQUIREMENTS**
- 5+ years of experience in a data engineering role
- Bachelor’s degree in relevant field
- Experience with data science in Python using Pandas, NumPy, Dask, and other data analysis libraries
- Use of data quality tools such as Great Expectations
- Experience working on Data Pipelines on AWS (Data Pipelines, S3, Athena)

**WILL BE A PLUS**
+ Machine learning related Python libraries (TensorFlow, PyTorch, Scikit-learn)
+ Team Leading experience

**RESPONSIBILITIES**
- Assemble large, complex data sets for processing by proprietary machine learning algorithms
- Perform all duties related to a data pipeline: ingestion, normalization, structuring, cleansing, validation, storage
- Write library code as well as custom code specific to a customer’s implementation
- Maintain a consistent process allowing for standardization across many customers’ data pipelines
- Communication with CTO, backend and AI teams

**PROJECT BENEFITS**
- The project brings innovation- AI core that provides the world’s first standardized productivity score
- Good quality of the codebase: we use unit testing, linters and code reviews
- Technical challenges