PySpark / Databricks Developer (Python | Airflow | Data Engineering)10829320

Itproposal; Amsterdam; Hybrid; EUR 70,000 - 110,000; Part time

Job summary

Itproposal is seeking an experienced PySpark/Databricks Developer to build scalable data pipelines and optimize distributed processing. You will work in an Agile environment with data engineers, product owners, and platform teams to deliver production-ready data solutions.

The role requires strong PySpark (Databricks) experience, Python development skills, and familiarity with orchestration tools such as Airflow. This is a hybrid position with partial on-site work in Amsterdam.

Qualifications

• 5+ years of hands-on PySpark (Databricks) experience.
• Strong Python development skills for data engineering.
• Experience with Agile delivery environments.

Responsibilities

• Develop, optimize, and maintain PySpark data pipelines on Databricks.
• Write clean, scalable Python code for data transformations and processing.
• Work with Airflow for scheduling and workflow management (preferred).
• Collaborate with cross-functional teams to refine requirements and deliver high-quality data solutions.
• Ensure data quality, reliability, and performance across all pipelines.
• Troubleshoot issues, perform root cause analysis, and implement fixes in production environments.
• Contribute to Agile ceremonies and support continuous improvement within the team.
• Document technical designs, data flows, and pipeline logic.

Skills

PySpark

Python

Airflow

Agile

Data Engineering

Communication

Tools

Databricks

Airflow

Azure DevOps

Job description

PySpark / Databricks Developer (Python | Airflow | Data Engineering)

Requirement ID: 10829320Location: Amsterdam, NetherlandsWork Mode: Partial Remote (2 days onsite, 3 days WFH)Start Date: ASAPDuration: 6 MonthsRate: NegotiableExperience: 6-8 YearsLanguage Requirement: EnglishStatus: Open

Role Overview

We are looking for an experienced PySpark / Databricks Developer with strong hands-on expertise in building scalable data pipelines, transforming large datasets, and optimizing distributed data processing workloads. You will work within an Agile environment, collaborating with data engineers, product owners, and platform teams to deliver high-quality, production-ready data solutions.

This role requires deep experience with PySpark on Databricks, strong Python development skills, and familiarity with orchestration tools such as Airflow (preferred). You will contribute to designing, developing, and maintaining data pipelines that support analytics, reporting, and downstream applications.

Key Responsibilities

• Develop, optimize, and maintain PySpark data pipelines on Databricks.
• Write clean, efficient, and scalable Python code for data transformations and processing.
• Work with orchestration tools such as Airflow for scheduling and workflow management (preferred).
• Collaborate with cross-functional teams to refine requirements and deliver high-quality data solutions.
• Ensure data quality, reliability, and performance across all pipelines.
• Troubleshoot issues, perform root cause analysis, and implement fixes in production environments.
• Contribute to Agile ceremonies and support continuous improvement within the team.
• Document technical designs, data flows, and pipeline logic.

Required Skills & Experience

• 5+ years of hands-on experience with PySpark (Databricks).
• Strong proficiency in Python for data engineering.
• Experience with Airflow (good to have, not mandatory).
• Solid understanding of distributed data processing and performance optimization.
• Experience working in Agile delivery environments.
• Strong communication skills and ability to collaborate with technical and non-technical stakeholders.

Competencies

• PySpark (Databricks)
• Python Development
• Data Engineering
• Airflow (Preferred)
• CI/CD & DevOps (Azure DevOps)
• Agile Way of Working