Senior Data Engineer Expert

5 hours ago


Remote Warsaw Warszawa, Czech Republic Sunscrapers Full time
Company Overview

Sunscrapers is a leading force in software development, expanding its presence in a data-centric environment. We are committed to helping clients grow and innovate through a comprehensive tech stack and robust data-related projects.

Job Description

We are seeking an experienced Senior Data Engineer to design and implement core systems that enable data science and data visualization at companies that implement data-driven decision processes to create a competitive advantage.

You will build data platforms for data and business teams, including internal tooling, data pipeline orchestrators, data warehouses, and more, using:

Technologies: Python, Terraform, SQL, Pandas, Shell scripts

Tools: Apache Airflow / Astronomer, GIT, Docker, Kubernetes, Snowflake, Pinecone, Neo4j, Jenkins, Jupyter Notebook, OpenAI API, Artifactory, Windows with WSL, Linux, Gitlab

AWS: EC2, ELB, IAM, RDS, Route53, S3, and more

Best Practices: Continuous Integration, Code Reviews

Required Skills and Qualifications

The ideal candidate will be well-organized, eager to constantly improve and learn, driven, and most of all - a team player.

Requirements include:

  • Data modeling
  • Terraform
  • Airflow
  • AWS
  • Docker
  • Python
  • SQL
  • Analytical skills
  • Kubernetes
  • Data visualization
  • Snowflake
  • Jupyter Notebook
  • Artifactory
  • Linux
  • GitLab
  • NumPy
  • SQLAlchemy
  • JFrog Artifactory
Benefits

What do we offer?

  • Working alongside a talented team of software engineers who are changing the image of Poland abroad
  • Culture of teamwork, professional development, and knowledge sharing
  • Flexible working hours and remote work possibility
  • Comfortable office in central Warsaw, equipped with all the necessary tools for conquering the universe
Others

This role involves delivering production-grade applications, creating solutions that enable data scientists and business analysts to be self-sufficient as much as possible, finding new ways to leverage Gen AI applications and underlying vector and graph data storages, designing datasets and schemes for consistency and easy access, contributing to data technology stacks including data warehouses and ETL pipelines, building data flows for fetching, aggregation, and data modeling using batch and streaming pipelines, documenting design decisions before implementation.



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