Data Analytics Engineer (ID3416)

Amsterdam - Netherlands

Monthly Salary: Not Disclosed

Experience Required: 6-8years

Posted on: 5 hours ago

Vacancies: 1 Vacancy

Job Summary

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:

68 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.

Lets Connect

Want to discuss this opportunity in more detail Feel free to reach out.

Recruiter: Vincee Venkatraman

Phone:; Extn :141

Email:

LinkedIn: Skills:

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: 68 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. Lets Connect Want to discuss this opportunity in more detail Feel free to reach out. Recruiter: Aswin Dhanvandhar Phone:; Extn :141 Email: LinkedIn:

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:

68 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.