Senior Data Engineer - Remote, AI-Powered Data Solutions

STX Next

Warszawa

On-site

PLN 165,000 - 276,000

Full time

14 days+
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Benefits offered by this job

Remote-first culture
Health/Ces
Flexible schedule

Job summary

STX Next, a global IT consulting company, is seeking a Data Engineer for a remote-first role serving international clients. You will transform data into valuable systems, shaping architecture and pipelines for reliable performance across large datasets and distributed systems.

Responsibilities include designing scalable data architectures, building ETL/data warehousing solutions, and ensuring high data quality.

Qualifications

  • Minimum 7 years of experience in Data Engineering.
  • Design scalable data processing systems including pipelines, ETL, data warehouses and data lakes.
  • Hands-on experience with Snowflake, Databricks or Apache Iceberg.
  • 3+ years of hands-on experience in AWS or Azure data services.
  • Practical experience with dbt for data transformation.
  • Strong SQL skills and experience with relational databases.
  • Familiarity with Apache Airflow for workflow orchestration.
  • Proficiency in Python for data engineering tasks.
  • Very good communication skills in English (min. B2).
  • AI native mindset.

Responsibilities

  • Develop innovative data solutions for complex challenges.
  • Design and build data systems to meet client requirements and optimize UX.
  • Collaborate across teams to integrate diverse approaches.
  • Serve as consultant and architect for global data solutions.
  • Handle large-scale data processing and distributed systems for reliability.

Skills

Data engineering
Snowflake
Databricks
Apache Iceberg
AWS
Azure
dbt
SQL
Apache Airflow
Python
English (B2)
AI mindset

Tools

Snowflake
Databricks
Apache Iceberg
dbt
Apache Airflow

Job description

STX Next, a global IT consulting company, is seeking a Data Engineer for a remote-first role serving international clients. You will transform data into valuable systems, shaping architecture and pipelines for reliable performance across large datasets and distributed systems.

Responsibilities include designing scalable data architectures, building ETL/data warehousing solutions, and ensuring high data quality.

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