Position: Data Engineer (AI-driven productivity score platform)
Company: SSA Group
Experience required: 3y
Category: Data Science
English level: upper
Published: 2021-10-01T00:00:00+03:00

PROJECT
Use your knowledge to build a complex cutting-edge product while working with highly skilled and experienced team members in a collaborative and friendly atmosphere. Design, code, configure, and document components that manage data ingestion, real-time streaming, batch processing, data extraction, and transformation.

This project is bringing a revolution to this field with its cutting-edge AI core 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.

TEAM
At SSA we have the following team: a Team Leader, QA, Senior DevOps, Back-end developer, Senior Front-end developer.

On the client’s side, there are 2 Data Scientists, Data Engineer, UI/UX Designer, Tech. Lead / Product Owner.

CANDIDATE REQUIREMENTS
4+ years of experience as a Data Engineer.
3+ years of programming experience with Python
1+ years of experience with AWS: EC2, S3, RDS
Hands-on experience on SQL and NoSQL (MongoDB) databases is a must.
Demonstrated Analytical ability, results-oriented environment with external customer interaction.
English level: Upper-Intermediate
Excellent written and verbal communication and presentation skills and the ability to express thoughts logically and succinctly.

WILL BE A PLUS
Bachelor’s degree in Computer Science, Engineering, Operations Research, Math, or related discipline.
Understanding of data warehousing, data modeling concept, and building new DW tables
AWS experience with Databricks, Spark, EMR, RDS, Redshift, Athena, and/or Glue
Statistics knowledge and hypothesis testing experience
Fluency in data analysis and communication around data, including time series analysis

RESPONSIBILITIES
Analyze and handle raw client data from CRM/ERP systems (like SalesForce, SAP, Oracle, etc.) and other activity logs of 3rd party systems
Design, development, and maintenance of data pipelines to prepare datasets for the data science team using Python
Handle results of machine learning for data presentation on the web portal
Generate synthetic data to test operability and performance of all parts of the system
Working with Data Scientists to set up continuous data processing

PROJECT BENEFITS
A strong friendly team
Modern technologies
Good quality of the codebase: we use unit testing, linters, and code reviews
The project brings innovation
Enterprise-level customers
Technical challenges