Data Engineering

Global Enterprise Partners

Amsterdam, Netherlands

21 days ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

1 year minimum

Working hours

Regular working hours

Job source

www.globalenterprisepartners.com

Tech stack

Agile Methodology Business Analytics Applications Data Analysis Microsoft Azure Big Data Cloud Computing Continuous Integration Data Architecture Information Engineering Data Governance Data Infrastructure Data Integration

+21 more

Extract Transform Load (ETL) Data Systems Data Warehousing DevOps Dimensional Modeling Fault Tolerance Github Python (Programming Language) Power BI Cloud Services DataOps SAP (Applications) Enterprise Data Management Azure Data Factory Pyspark Data Analytics Machine Learning Operations Data Delivery Azure Synapse Analytics Data Pipelines Databricks

Job description

Design, develop, and enhance enterprise-scale data pipelines and analytics solutions. Build scalable cloud data platforms supporting reporting, analytics, and data science initiatives. Implement DataOps, DevOps, and MLOps best practices. Deliver high-quality, fault-tolerant data solutions that improve performance and reduce operational costs. Collaborate with Data Scientists, Architects, Business Users, and Analytics teams to deliver business value. Support enterprise data governance, integration, and quality initiatives. Mentor and support junior engineers and project teams. Contribute to continuous improvement of data architecture, standards, and ways of working.

Requirements

3-10+ years of experience within Data Engineering, Data Warehousing, Business Intelligence, or Analytics environments. Strong hands-on experience with:

Microsoft Azure Azure Data Factory Azure Synapse Analytics Databricks SQL Python PySpark SAP Datasphere Power BI

Experience building and maintaining cloud-based ETL/ELT data pipelines. Strong understanding of data warehousing concepts, dimensional modelling, and data integration best practices. Experience working with Azure DevOps, GitHub, and CI/CD practices. Experience working within Agile, DevOps, or DataOps environments. Strong problem-solving skills with the ability to optimise data delivery, reliability, and performance. Excellent communication and stakeholder management skills. Experience mentoring junior engineers or leading technical teams is highly desirable., 3+ years of Data Engineering experience. Experience developing Azure-based data solutions and ETL pipelines.

Senior Data Engineer

7+ years of Data Engineering experience. Advanced Azure Data Platform expertise. Experience leading deliveries and mentoring engineering teams.

Technical Lead

9+ years of Data Engineering and Analytics experience. Strong background delivering enterprise data warehouse and analytics projects. Experience leading stakeholders, delivery teams, and multiple concurrent projects. Expertise in data architecture, governance, modelling, and enterprise data integration.