Must have

• Python

• Apache Airflow

• SQL

• ETL

• XML

• REST API

• Data engineering

• Relational database

• MySQL

• English (B2)

• Polish (C1)

Nice to have

• Docker

• Web development

• TypeScript

• React

• Nest.js

• Bash

• SharePoint

• DevOps

• Kubernetes

• CI/CD

• Confluence

• Vault

• Snowflake

• JavaScript

• GraphQL

Requirements description

Technical Skills:

• Strong knowledge of Python, especially for ETL processes and data transformation.
• Experience with workflow orchestration tools, preferably Apache Airflow.
• Solid SQL skills and experience designing, querying, and administering relational databases (e.g., MySQL), including user access management and schema design.
• Hands-on experience working with REST APIs, API integration, and reading technical documentation.
• Good understanding of ETL processes, data pipelines, and data warehouse concepts.

Soft Skills:

• Ability to collaborate with both technical teams and business users.
• Strong organizational skills and ability to manage tasks independently.
• Clear and structured documentation and communication style.

Nice to Have:

• Experience in the energy, financial, or trading industry.
• Experience with DevOps tools such as Docker, Kubernetes, and CI/CD pipelines.
• Basic knowledge of web development (JavaScript, TypeScript, React, Nest.js or similar frameworks) for building or supporting data-driven applications.

Offer description

We are looking for a versatile and technically skilled Data Engineer who will support data integration, backend development and process automation across multiple business domains. You will be working closely with DevOps, and Business stakeholders to drive the implementation of data workflows, backend features, and platform improvements.

This is a hands-on role ideal for someone who thrives in a cross-functional environment and enjoys building robust solutions end-to-end.

Your responsibilities

1. Develop and maintain Python scripts for data extraction, transformation, and loading (ETL).
2. Build and manage automated data workflows using Apache Airflow.
3. Analyze and transform data from various sources.
4. Design and create database views to meet business requirements.
5. Create reports and report-generation tools based on data stored in the data warehouse.
6. Work closely with traders and business stakeholders to gather requirements for data transformations and new calculations.

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