Analytics Engineer: Data Modeling & AI-Ready Pipelines

Meyandy LLC; Germany (OH); Hybrid; USD 81,000 - 127,000; Full time

Benefits offered by this job

Hybrid work

Career & training opportunities

International team

Social events

Mental health support

Job summary

Statista in Hamburg or Berlin is seeking an Analytics Engineer to design, build, and optimize scalable data models using modern data stack tools such as dbt and Snowflake. You will transform raw data into clean datasets for analytics, reporting, and operational use, collaborating with data engineers, analysts, and business stakeholders.

You’ll implement data quality checks, develop semantic layers, and promote data governance.

Qualifications

• 3+ years of experience in analytics engineering or data engineering.
• Strong SQL skills and data modeling experience (dimensional modeling, star schemas).
• Hands-on with modern data stack tools (dbt, CI/CD) and AI-assisted development workflows.
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift).
• Excellent written and verbal English; German is a plus.

Responsibilities

• Design, build, and optimize scalable data models using modern data stack tools (e.g., dbt, Snowflake).
• Transform raw data into clean, reliable datasets for analytics, reporting, and operational use.
• Collaborate with data engineers, analysts, tracking teams, and business stakeholders to define data requirements.
• Implement and maintain data quality checks, testing, and monitoring for accuracy and reliability.
• Develop and manage semantic layers to standardize key business metrics.
• Improve data accessibility and promote best practices and clear data structures.
• Document data models, definitions, and workflows to enhance transparency and literacy.

Skills

SQL

Data Modeling

dbt

CI/CD

Cloud Data Warehouses

English Communication

Tools

dbt

Snowflake

BigQuery

Redshift

CI/CD

Job description

Statista in Hamburg or Berlin is seeking an Analytics Engineer to design, build, and optimize scalable data models using modern data stack tools such as dbt and Snowflake. You will transform raw data into clean datasets for analytics, reporting, and operational use, collaborating with data engineers, analysts, and business stakeholders.

You’ll implement data quality checks, develop semantic layers, and promote data governance.