Senior Data Analytics Engineer

Infinity Quest; Amsterdam; Hybrid; EUR 70,000 - 100,000; Full time

Job summary

Infinity Quest is seeking a hybrid Data Engineer/Analytics Engineer to design and maintain scalable data pipelines and data warehouses in a complex data environment. The role requires translating business requirements into reliable datasets, dashboards, and actionable insights.

The ideal candidate has strong SQL, Python, Snowflake, and cloud skills, plus experience with dbt, data modelling, and data quality.

Qualifications

• Extensive experience designing and maintaining scalable data pipelines and ETL processes.
• Strong SQL, Python, and cloud technologies in data platforms.
• Experience translating business requirements into reliable datasets, dashboards, and insights.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL processes.
• Work with complex datasets to identify trends and actionable insights.
• Design and optimize databases and data warehouses for performance and scalability.
• Collaborate with stakeholders to understand requirements and deliver data solutions.
• Implement data quality checks, validation, monitoring, and data-management best practices.
• Work with SQL, Python, Snowflake, dbt, and cloud technologies.
• Support data architecture and system-design initiatives.
• Contribute to analytics and visualization solutions supporting data-driven decision-making.
• Follow engineering best practices, including version control and CI/CD.

Skills

Advanced SQL

dbt/Data Build Tool

Python

Snowflake

AWS

Data Warehousing

Data Modelling

Data Quality

System Design

Snowflake Semantic Views

CI/CD

Job description

Employment Type: Fixed Term Contract - 1year

Hybrid : – 2–3 days per week from office

This hybrid role combines Data Engineering, Analytics Engineering, and senior technical responsibilities. In addition to building data pipelines, the candidate should be able to translate business requirements into reliable datasets, dashboards, and actionable insights. Please share only profiles with both Data Analytics and Data Engineering experience.

Job Description / Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL/data transformation processes.
• Work with complex datasets to identify trends and actionable business insights.
• Design and optimize databases and data warehouses for performance and scalability.
• Collaborate with business and technical stakeholders to understand requirements and deliver appropriate data solutions.
• Implement data quality checks, validation, monitoring, and data-management best practices.
• Work extensively with SQL, Python, Snowflake, dbt, and cloud technologies.
• Support data architecture and system-design initiatives.
• Contribute to analytics and visualization solutions supporting data-driven decision-making.
• Follow engineering best practices, including version control and CI/CD.

Mandatory Skills:

• Advanced SQL
• dbt / Data Build Tool
• Python
• Snowflake
• AWS
• Data Warehousing & Data Modelling
• Data Quality
• System Design
• Snowflake Semantic Views
• CI/CD

Key Skills:

Advanced SQL, dbt, Python, Snowflake, Data Architecture/System Design, Data Quality, Data Warehousing Concepts, and Data Modeling.