Data Engineer: Spark, Python & Cloud Data Pipelines

Enfint; Łódź; On-site; PLN 102,000 - 122,000; Full time

Benefits offered by this job

Private medical care

Kafeteria MyBenefit credits

Multisport membership

Glasses reimbursement

Referral bonuses

AI tools licenses (GitHub Copilot, etc

Job summary

Vention in Poland is seeking an experienced Data Engineer to design and maintain scalable data pipelines and analytics-ready data stores. You will work across cloud platforms, Spark-based processing, and collaborate with cross-functional teams to turn business needs into reliable data solutions.

This role offers hands-on tooling with modern data architectures and opportunities to contribute to AI-driven projects and data-driven decision making within a dynamic engineering team.

Qualifications

• 4+ years of experience in Data Engineering delivering end-to-end data solutions.

Responsibilities

• Build, optimize, and maintain scalable ETL/ELT pipelines on cloud platforms.
• Integrate data sources ensuring data quality, reliability, and accessibility for analytics.
• Design and maintain cloud-native data architectures, including Data Lake, Data Warehouse, and Data Lakehouse.
• Develop data processing solutions using Spark and PySpark in distributed environments.
• Collaborate with cross-functional teams to translate business requirements into efficient, scalable data solutions.
• Support analytics use cases by enabling data consumption for reporting, dashboards, and visualization tools.
• Stay up to date with modern data platform technologies and best practices, contributing to continuous improvement of the data ecosystem.

Skills

Python

SQL

Agile

English (B2+)

Tools

Apache Spark

PySpark

AWS

S3

Glue

Athena

QuickSight

Azure

Data Factory

Databricks

ADLS

Data Lake

Delta Lake

Data Warehouse

Scrum

Kanban

Job description

Vention in Poland is seeking an experienced Data Engineer to design and maintain scalable data pipelines and analytics-ready data stores. You will work across cloud platforms, Spark-based processing, and collaborate with cross-functional teams to turn business needs into reliable data solutions.

This role offers hands-on tooling with modern data architectures and opportunities to contribute to AI-driven projects and data-driven decision making within a dynamic engineering team.