Data Engineer

Hello everyone!

We are looking for a Data Engineer to join our team and help build and maintain modern data pipelines.

We’re seeking a Data Engineer to join our growing team. You’ll work with our data infrastructure built on AWS, focusing on data transformation, pipeline development, and database management.

This is an excellent opportunity to grow your skills in a fast-paced startup environment while working with modern data technologies.

Project Idea

As a Data Engineer, you will work directly with the company’s data infrastructure built on AWS. Your focus will be on data transformation, pipeline development, and database management, ensuring that data is reliable, scalable, and accessible for business needs. You’ll get hands-on experience with AWS services (S3, RDS, EC2), contribute to building efficient ETL/ELT processes, and help optimize how data flows across the organization. This is a great opportunity to grow your skills in cloud-based data engineering while collaborating with a U.S.-based client and an international team.

What is the team size and structure?

You’ll be joining a growing team that includes an Architect, a Senior Node.js Engineer, and a Project Manager, working in close collaboration with the client.

How many stages of the interview are there?

• Interview with the Recruiter — up to 30 min.
• Cultural interview — up to 1 hour.
• Technical interview — up to 1 hour.
• Call with the client (optional) — up to 1 hour.

Requirements:

• 1-3 years of experience in data engineering or related field;
• Strong proficiency in PostgreSQL;
• Solid Python programming skills — experience with data manipulation libraries (pandas, numpy);
• SQL expertise;
• Experience with AWS core services (S3, RDS, EC2);
• Understanding of data pipeline concepts and ETL/ELT processes;
• Familiarity with version control (Git) and collaborative development practices;
• Upper-intermediate or higher level of English.

Responsibilities:

• Build and maintain data integrations using Python for ETL/ELT processes
• Write efficient SQL queries to extract, transform, and analyze data across PostgreSQL and Snowflake
• Collaborate with the engineering team to ensure data quality and reliability
• Work with AWS services including S3, RDS, and EC2 to support data infrastructure
• Collect and consolidate data from various sources, including databases and REST API integrations, for further analysis
• Participate in code reviews and follow best practices for data engineering
• Monitor data pipeline performance and troubleshoot issues as they arise