Data & Analytics Engineer (m/f/d)

Meyandy LLC

Germany (OH)

On-site

USD 81,000 - 115,000

Full time

14 days+

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Benefits offered by this job

Hybrid work

International team

Career & training

Mental health support

Langdock access

Job summary

Statista in Germany is seeking a Data & Analytics Engineer to design, implement, and maintain backend data services powering our data access layer. You will work across data pipelines, ensure robust data models, and collaborate with analytics teams.

You will build CI/CD pipelines on AWS/Kubernetes, manage Kafka schemas, and enable data access in Snowflake and via APIs, while aligning with business requirements and governance standards.

Qualifications

3+ years of experience in analytics engineering, data engineering, or a related role.
Strong SQL skills and solid experience in data modeling (e.g., dimensional modeling, star schemas).
Hands-on experience with event streaming and message distribution, ideally Kafka, including schema management with the Kafka schema registry (Avro, Protobuf, or JSON Schema).
Experience designing data contracts and schemas between upstream producers and downstream consumers.
Experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and modern data stack tools (e.g., dbt, CI/CD).
Openness to AI-assisted development workflows (e.g., Claude Code or similar).
Comfort working at the boundary of streaming/operational data and analytical data models, and building access layers that serve applications via API.
Strong attention to detail with a quality-focused and structured working style.
Interest in data governance, standards, and scalable data architecture.
Analytical mindset with strong problem-solving skills.
Excellent communication skills in English (German is a plus), with both technical and business stakeholders, combined with a solid understanding of business requirements and contexts.

Responsibilities

Design, implement, and maintain backend services in Python that power our data access and distribution layer.
Build and operate automated build, test, and deployment pipelines following CI/CD and GitOps practices, running on AWS and Kubernetes.
Design and maintain data models and schemas (Avro, SQL) for our data pipelines and services, and publish them to downstream consumers via our Kafka-based distribution platform and schema registry.
Build access-layer data models in our analytics environment (e.g., Snowflake) so applications can work with the data directly, including via API.
Act as the coordination interface between the Data and Tech divisions, aligning priorities, schemas, and timelines across upstream and downstream teams.

Skills

SQL

Analytics engineering

Kafka

Data modeling

Cloud data warehouses

dbt

CI/CD

Tools

Snowflake

BigQuery

Redshift

Kafka Schema Registry

Job description

At Statista, we’re all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions. Founded in Hamburg in 2007, we have quickly grown into a global company with offices in major cities such as London, New York, Berlin and Tokyo. And we still have a lot of plans. Our constant growth does not only prove our success, but also keeps creating new development and career opportunities for our employees. We value and celebrate our diverse culture. You are welcome here for who you are, no matter where you come from, what you look like, or whether you prefer bar graphs to pie charts. Your story matters – keep writing it as part of our team.

Your role

Design, implement, and maintain backend services in Python that power our data access and distribution layer
Build and operate automated build, test, and deployment pipelines following CI/CD and GitOps practices, running on AWS and Kubernetes
Design and maintain data models and schemas (Avro, SQL) for our data pipelines and services, and publish them to downstream consumers via our Kafka-based distribution platform and schema registry
Build access-layer data models in our analytics environment (e.g., Snowflake) so applications can work with the data directly, including via API
Act as the coordination interface between the Data and Tech divisions, aligning priorities, schemas, and timelines across upstream and downstream teams

Your profile

3+ years of experience in analytics engineering, data engineering, or a related role.
Strong SQL skills and solid experience in data modeling (e.g., dimensional modeling, star schemas).
Hands-on experience with event streaming and message distribution, ideally Kafka, including schema management with the Kafka schema registry (Avro, Protobuf, or JSON Schema).
Experience designing data contracts and schemas between upstream producers and downstream consumers.
Experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and modern data stack tools (e.g., dbt, CI/CD).
Openness to AI-assisted development workflows (e.g., Claude Code or similar).
Comfort working at the boundary of streaming/operational data and analytical data models, and building access layers that serve applications via API.
Strong attention to detail with a quality-focused and structured working style.
Interest in data governance, standards, and scalable data architecture.
Analytical mindset with strong problem-solving skills.
Excellent communication skills in English (German is a plus), with both technical and business stakeholders, combined with a solid understanding of business requirements and contexts.

What we offer

In addition to our great team, culture, and our shared goal of empowering people with data, there are many other things that make Statista a great place to work! Join us and benefit from: