Middle Data Engineer for AI-driven employee productivity score platform Offline

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 Analytics, UI/UX Designer, Tech. Lead / Product Owner.

CANDIDATE REQUIREMENTS

4+ years of programming experience with Python

2+ years of experience with ETL pipelines (Pandas)

1+ years of experience with AWS: EC2, S3, RDS

Hands-on experience on SQL (e.g. PostgreSQL) and NoSQL (e.g. MongoDB) databases

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

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

Create and maintain optimal data pipeline architecture

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies

Work in close collaboration with Product Owner

Collaborate with Data Analytics and Data Scientists to strive for greater functionality in data systems

Follow best practices in software development

Maintain documentation and test coverage

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