APSS ISR Data Engineering

Vector Synergy; Den Haag; On-site; EUR 65,000 - 90,000; Full time

Job summary

Vector Synergy is seeking a data integration specialist to design and implement ETL processes that connect diverse data sources across networks and domains. You will develop pipelines, mappings, and schemas to ensure data consistency and accuracy across platforms.

The role requires 1–3+ years of hands-on experience with modern ETL tools, data modelling, and working with cloud services and multiple databases. You will troubleshoot data flow issues in production to maintain reliability.

Qualifications

• 1–3+ years in implementing data integration patterns with modern ETL tools.
• 1–3+ years practical experience in data modelling and transformation to ingest data from heterogeneous sources.
• 1–3+ years experience with data sharing platforms, object stores, and varied databases (Relational, NoSQL, Graph, Object).

Responsibilities

• Design ETL processes to connect data sources across networks and domains.
• Develop data pipelines, mappings, and schemas to ensure data consistency.
• Investigate and resolve data flow bottlenecks in production environments.

Skills

ETL tools

Data modelling

Data transformation

Cloud services

Databases

Data sharing

Tools

Apache NiFi

Informatica

Talend

SSIS

Job description

• 1-3+ years proficiency in implementing data integration patterns with modern ETL tools (e.g., Apache NIFI, Informatica, Talend, SSIS), especially in the context of cloud services (AWS, Azure) ;
• 1-3+ years practical experience in data modelling and transformation to ingest and integrate data from heterogeneous data sources and systems ;
• 1-3+ years experience with data sharing platforms, object stores, and various types of databases, (Relational, NoSQL, Graph, Object, Vector).

Duties/role:

• Designing and implementing extraction, transformation, and loading processes to connect various data sources across different networks and domains;
• Developing data pipelines, transformation mappings, and data schemas to enable data centricity and ensure data consistency and accuracy across platforms;
• Investigating and resolving data flow bottlenecks and technical issues in production environments .