Hybrid Analytics Engineer: Data Pipelines & Insights

Stitchd; Arnhem; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

MacBook Pro

Hospitalisation insurance

Pension plan

Flexible working hours

Job summary

Stitchd is seeking an Analytics Engineer to design and maintain robust data pipelines and analytics-ready datasets. You will enable insights and activation by partnering with marketing, business and IT teams.

You will build scalable data models and leverage modern data warehouses like Snowflake, Databricks or BigQuery, while using Python and Git for data manipulation and version control. Hybrid work from NL/BE offices is offered.

Qualifications

• Strong SQL with advanced aggregations, window functions and query optimization.
• Experience designing efficient, scalable data models.
• Experience with modern data warehouses (Snowflake, Databricks, BigQuery).
• Experience with ELT/ETL pipelines.
• Proficiency in Python for data manipulation and automation.
• Experience using Git for version control.

Responsibilities

• Design, build and maintain robust ETL/ELT pipelines transforming raw data into analytics-ready datasets.
• Design and maintain clear, scalable data models for analytics and activation use cases.
• Implement data quality checks and monitoring to ensure accuracy and reliability.
• Translate business questions into concrete data solutions and ownership.
• Collaborate with analysts, marketing, IT to enable insights and activation.
• Stay up-to-date with data technologies and improve the data stack.

Skills

Advanced SQL

Python

Data modeling

Data warehousing

ETL/ELT pipelines

Git

Tools

Snowflake

Databricks

BigQuery

Tableau

Power BI

Looker Studio

Job description

Stitchd is seeking an Analytics Engineer to design and maintain robust data pipelines and analytics-ready datasets. You will enable insights and activation by partnering with marketing, business and IT teams.

You will build scalable data models and leverage modern data warehouses like Snowflake, Databricks or BigQuery, while using Python and Git for data manipulation and version control. Hybrid work from NL/BE offices is offered.