Data Engineer - Azure Data Marketplace @ Belvedere Recruitment

Belvedere Recruitment; Warszawa; Hybrid; PLN 335,000 - 469,000; Part time

Job summary

Belvedere Recruitment in Warsaw seeks an experienced Data Engineer at Manager level for a 3-month hybrid contract. You will design, build and optimise data ingestion pipelines using Azure Data Factory and Azure Databricks, shaping enterprise-scale data products.

The role requires 8–10 years' experience in data engineering, strong Python/PySpark/SQL skills, and a proven ability to work across cross-functional teams to deliver reliable, scalable data solutions.

Qualifications

• 8-10 years of experience in data engineering roles.
• Expert knowledge of Azure Data Factory pipeline development and management.
• Proficiency with Azure Databricks, notebooks, jobs and clusters.
• Strong programming skills in Python, PySpark and SQL.
• Experience with Apache Spark for big data processing.
• Knowledge of ETL processes and data transformation techniques.
• Familiarity with Azure storage solutions including SQL Database, Blob Storage and Data Lake Storage.
• Understanding of data warehousing principles and scalable data modelling.
• Experience with PL/SQL.
• Ability to write modular, testable and maintainable code.
• Strong collaboration and communication skills.
• Experience working in cross-functional team environments.

Responsibilities

• Identify and develop opportunities to improve data assets and services.
• Design and build data ingestion pipelines focused on stability and optimisation.
• Develop, test and maintain robust data pipelines and processes.
• Write resilient, fault-tolerant and modular code for high availability.
• Research and implement new methods to build world-class data products.
• Collaborate across Ingestion, Consumption and Activation teams.
• Manage Azure Data Factory pipelines, activities, triggers and data flows.
• Process large datasets using Azure Databricks and Apache Spark.
• Transform and integrate data from multiple sources.
• Ensure data pipeline traceability and monitoring.

Skills

Azure Data Factory

Python

PySpark

SQL

Apache Spark

ETL

Data warehousing

PL/SQL

Modular code

Collaboration

Cross-functional teams

Databricks

Tools

Azure Databricks

Databricks notebooks

Databricks jobs

Databricks clusters

Azure Storage

SQL Database

Blob Storage

Data Lake Storage

Job description

• 8-10 years of experience in data engineering roles
• Expert knowledge of Azure Data Factory pipeline development and management
• Proficiency with Azure Databricks, notebooks, jobs and clusters
• Strong programming skills in Python, PySpark and SQL
• Experience with Apache Spark for big data processing
• Knowledge of ETL processes and data transformation techniques
• Familiarity with Azure storage solutions including SQL Database, Blob Storage and Data Lake Storage
• Understanding of data warehousing principles and scalable data modelling
• Experience with PL/SQL
• Ability to write modular, testable and maintainable code
• Strong collaboration and communication skills
• Experience working in cross-functional team environments

Location: Warsaw

Contract Type:3 Months

Job Type: Hybrid

• Work on cutting-edge AI data marketplace technology


• Lead data ingestion pipelines using Azure Data Factory and Databricks


• Manager-level contract role with 8-10 years' experience required


• Collaborate across teams on enterprise-scale data solutions


• Shape world-class data products and services

Company Overview

Our client is a global professional services organisation delivering technology-enabled solutions across consulting, advisory and assurance services. They are building an advanced AI-powered data marketplace platform designed to transform how data assets are created, managed and consumed across the enterprise. The organisation invests heavily in innovation and technology, creating opportunities for experienced engineers to work on meaningful projects that impact business operations globally. Their commitment to professional development and collaborative working environment makes them an employer of choice for data engineering professionals.

They are seeking an experienced Data Engineer at Manager level to join their AI Data Marketplace team in Warsaw. This contract role offers the opportunity to work on sophisticated data ingestion pipelines using Azure technologies whilst contributing to the development of enterprise-scale data products.

Position Overview

As a Data Engineer, you will play a central role in developing and maintaining the data ingestion infrastructure for the AI Data Marketplace platform. You will design, build and optimise data pipelines that ensure stability, traceability and performance across the platform. Working collaboratively with cross-functional teams, you will help shape how data assets are created and consumed, directly impacting the quality and reliability of services delivered to internal stakeholders. This role combines technical expertise with strategic thinking to continuously improve data products and processes.

Benefits

Whilst specific benefits details are being confirmed, you'll join a globally recognised organisation that values professional development and technical excellence. You'll be immersed in a collaborative environment working alongside skilled engineers and data specialists on meaningful projects that advance AI and data marketplace capabilities.

Responsibilities

• Identify and develop opportunities to improve data assets and services


• Design and build data ingestion pipelines focused on stability and optimisation


• Develop, test and maintain robust data pipelines and processes


• Write resilient, fault-tolerant and modular code for high availability


• Research and implement new methods to build world-class data products


• Collaborate across Ingestion, Consumption and Activation teams


• Manage Azure Data Factory pipelines, activities, triggers and data flows


• Process large datasets using Azure Databricks and Apache Spark


• Transform and integrate data from multiple sources


• Ensure data pipeline traceability and monitoring

Requirements

Azure Data Factory, Azure Databricks, Python, PySpark, SQL, Apache Spark, ETL, Data Lake, Data modelling