The Role
Design, build, and maintain scalable data pipelines and analytics-ready datasets. Implement Data Vault models in Snowflake, write and optimize complex SQL/PLSQL, automate processes with Python, use DBT for transformations, monitor production pipelines, and collaborate with cross-functional data teams to deliver data products and high-quality reporting datasets.
Summary Generated by Built In
As a Data Analytics Engineer, you will:
- Bridge the gap between data engineering, data architecture, and data analysis by delivering clean, reliable, and analytics-ready data.
- Design, build, and maintain robust and scalable data pipelines to support repeatable and accessible data consumption.
- Transform raw data into structured, high-quality datasets suitable for analysis and reporting.
- Develop and maintain complex data models that represent business processes and entities.
- Implement flexible Data Vault models in Snowflake to support large-scale analytics and business intelligence.
- Write, optimize, and maintain complex SQL queries with a focus on performance, scalability, and data integrity.
- Monitor, troubleshoot, and proactively resolve issues in production data pipelines.
- Automate repetitive data processes using Python and scripting tools to improve efficiency and scalability.
- Collaborate closely with Data Engineers, Data Architects, Data Scientists, and Product Managers to deliver integrated data solutions.
- Contribute to the design and development of data products, enhancing existing components or creating new ones as needed.
What You Bring to the Table:
- 6–8 years of experience in data analytics engineering, data engineering, or advanced analytics roles.
- Strong expertise in SQL and PL/SQL for data transformation and performance optimization.
- Hands-on experience with Snowflake and modern cloud data warehouses.
- Solid experience implementing Data Vault modelling techniques.
- Proficiency in Python for automation and data workflow orchestration.
- Experience with DBT (Data Build Tool) for data transformation and modelling.
- Strong understanding of data warehousing concepts and data modelling principles.
- Proven ability to work with complex and high-volume datasets.
You Should Possess the Ability to:
- Translate business requirements into scalable, technical data solutions.
- Design and maintain analytics-ready datasets and reusable data models.
- Optimize data workflows for performance, reliability, and scalability.
- Automate data operations to improve efficiency and consistency.
- Influence design decisions aligned with architectural and engineering standards.
- Adapt to evolving technologies, tools, and analytics best practices.
What We Bring to the Table:
- Opportunity to work on complex, end-to-end data products.
- Exposure to modern data platforms and modelling techniques.
- A collaborative environment that values data quality, scalability, and innovation.
- The chance to influence data solutions that support business-critical insights.
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Vincee Venkatraman
Phone: +31 20 369 0609 ; Extn :141
LinkedIn:https://www.linkedin.com/in/vincee-venkatraman-aa5a24293/
Skills Required
- 6-8 years of experience in data analytics engineering, data engineering, or advanced analytics roles.
- Strong expertise in SQL and PL/SQL for data transformation and performance optimization.
- Hands-on experience with Snowflake and modern cloud data warehouses.
- Solid experience implementing Data Vault modelling techniques.
- Proficiency in Python for automation and data workflow orchestration.
- Experience with DBT (Data Build Tool) for data transformation and modelling.
- Strong understanding of data warehousing concepts and data modelling principles.
- Proven ability to work with complex and high-volume datasets.
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The Company
What We Do
STAFIDE is a Netherlands-based niche technology talent consulting company operating across Europe. It helps organizations identify, recruit, and deploy technology professionals in areas including cybersecurity, cloud engineering, software development, data analytics, ERP, infrastructure, and digital transformation. Its services include recruitment, workforce engagement, secondment, onboarding support, workforce deployment, and workforce analytics that support technology hiring and expansion.
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