Data & Analytics Engineer — Hybrid & Growth Opportunities

Statista Inc.; Germany (OH); Hybrid; USD 100,000 - 160,000; Full time

Benefits offered by this job

Hybrid work & flex-time

International team

Social events

Career & training opportunities

Mental health support

Job summary

Statista Inc. is seeking an analytics engineer to design, implement, and maintain backend Python services powering data access and distribution.

You will build automated CI/CD pipelines on AWS and Kubernetes and craft data models to support downstream consumers via a Kafka-based platform and schema registry. Responsibilities include developing data contracts, modeling schemas for analytics and API access, and coordinating with Data and Tech teams to align priorities and timelines across upstream

Qualifications

• 3+ years of experience in analytics engineering, data engineering, or a related role.
• Strong SQL skills and data modeling (dimensional modeling, star schemas).
• Hands-on experience with event streaming and message distribution, especially Kafka, including schema management.

Responsibilities

• Design, implement, and maintain backend Python services powering data access and distribution.
• Build and operate CI/CD pipelines on AWS and Kubernetes.
• Design data models for pipelines and publish to downstream consumers via Kafka and schema registry.
• Create data models in analytics environment (e.g., Snowflake) and expose data via API.
• Coordinate between Data and Tech divisions to align priorities and timelines.

Skills

SQL

Analytics engineering

Data modeling

English communication

Problem solving

Tools

Kafka

Kafka schema registry

Snowflake

BigQuery

Redshift

dbt

CI/CD

AWS

Kubernetes

Job description

Statista Inc. is seeking an analytics engineer to design, implement, and maintain backend Python services powering data access and distribution.

You will build automated CI/CD pipelines on AWS and Kubernetes and craft data models to support downstream consumers via a Kafka-based platform and schema registry. Responsibilities include developing data contracts, modeling schemas for analytics and API access, and coordinating with Data and Tech teams to align priorities and timelines across upstream