Senior Data Engineer - Hot

The CHI Software team is not standing still. We love our job and give it one hundred percent of us! Every new project is a challenge that we face successfully. The only thing that can stop us is… Wait, it’s nothing! The number of projects is growing, and with them, our team too. And now we need a Senior Data Engineer.

We are seeking a skilled and experienced Data Engineer. The ideal candidate will be deeply involved in discovering, analyzing, and assembling large and complex data sets. They will design and build our big data infrastructure, ensure data security, and optimize the performance of our big data platforms, primarily within the AWS cloud environment.

Requirements:

At least 4 years of experience in building, optimizing, and maintaining big data pipelines and architectures;
Strong proficiency in Python;
Hands-on experience with ETL pipeline construction in an AWS environment;
Familiarity with AWS services such as AWS Lambda, Amazon EventBridge, Amazon S3, Amazon Kinesis, and AWS Step Functions;
Experience with ELK stack or OpenSearch platforms;
Solid understanding of data security and implementing access controls in the AWS cloud platform;
A clear grasp of Data Warehouse architecture concepts.

Responsibilities:

Discover, analyse, and assemble large, complex data sets to meet functional and non-functional business requirements;
Design, build, optimize, and maintain robust ‘big data’ data pipelines, architectures, and datasets;
Build scalable ETL pipelines for various data sources using Python in the AWS ecosystem;
Engage with AWS services including AWS Lambda, Amazon EventBridge, Amazon S3, Amazon Kinesis, and AWS Step Functions;
Implement and manage ELK stack or OpenSearch-based platforms;
Ensure robust data security measures and access controls are implemented across our AWS data infrastructure;
Collaborate with team members to improve existing systems, streamline processes, and drive data-related initiatives;
Understand and leverage the architecture of data warehouses for optimal performance;
Troubleshoot and resolve data issues, ensuring data accuracy and reliability;
Collaborate effectively with cross-functional teams, presenting data findings and insights when required.