Position: Senior Data Engineer with Python and AWS
Company: DataArt
Category: Data Engineer
Experience required: 3y
English level: intermediate

The company would like to rebuild 2 existing SaaS applications using cutting-edge technologies for future scaling and extension of functionality.
Most work will be on new and/or relatively recent codebases. The core stack of technology - Python, AWS.

**Client**
The Company is an information and billing services provider to the Direct Store Delivery (DSD) sector.  The client provides services to small format retail stores of national chains, along with their last-mile logistics providers delivering fresh, fast-moving, and delicate goods on a just-in-time basis, as well as national CPG companies.

The company is primarily a software technology business with a B2B SaaS delivery model.

**Position Overview**
We are looking for a mature and highly skilled Data Engineer with Python and AWS skills.
The Backend Engineer position is focused on the Company's APIs and data platform. Day-to-day work will include designing new APIs, libraries, and subsystems, refactoring for scale and performance, and building, testing, deploying and supporting production quality code. This position will work primarily on a new clean-room implementation of a highly successful product.

**Technology Stack**
*	Python
*	AWS
*	Spark
*	Kafka
*	Redshift

**Requirements**
- 4+ years of experience or over 5 completed projects
- Experience with Python and strong knowledge of its best practices
- Experience working with PySpark (AWS Glue)
- Experience working with AWS services: Glue, MSK (or Kafka), Redshift, S3
- Familiarity with any IaC provision tools: Terraform or CloudFormation
- Knowledge of data management fundamentals (DWH theory , data modeling, ELT/ETL, data quality, metadata management, distributed systems)
- Knowledge of SQL (DDL part)
- Knowledge of backend development in general
- Strong written and verbal English communications

**Nice to have**
- Knowledge of data management fundamentals and data engineering