Statista

2 days ago

Data & Analytics Engineer (m/f/d)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Design, implement, and maintain Python backend services that power a data access and distribution layer. Build and run CI/CD and GitOps pipelines on AWS and Kubernetes. Develop data models and schemas (Avro, SQL) and publish them via a Kafka-based distribution platform and schema registry. Create Snowflake-based access-layer models for application APIs, and coordinate priorities between Data and Tech teams.

Location: Hamburg, Berlin

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Design, implement, and maintain Python backend services for the data access and distribution layer.
•Build and operate automated build, test, and deployment pipelines using CI/CD and GitOps on AWS and Kubernetes.
•Design and maintain data models and schemas (Avro, SQL), publishing them to downstream consumers via Kafka and a schema registry.
•Build access-layer data models in analytics environments (e.g., Snowflake) so applications can work with data via API.
•Coordinate between Data and Tech divisions to align priorities, schemas, and timelines across upstream and downstream teams.

Pay and Benefits

Perks:Hybrid WorkHealth InsuranceGym Membership

Key Requirements

•3+ years of experience in analytics engineering, data engineering, or a related role.
•Strong SQL skills and experience with 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.
•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).

Experience:3+ yearsData engineeringAnalytics engineering

Skills:CommunicationAttention to detailQuality-focusedProblem-solvingAnalytical mindset

Languages:EnglishGerman

Tech Stack:PythonCI/CDGitOpsAWSKubernetesAvroSQLKafkaSchema registryProtobufJSON SchemaSnowflakeBigQueryRedshiftDbtClaude CodeAPI

Company Brief

Statista

Operates an online statistics portal providing market and consumer data, industry reports, and infographics. Serves businesses, researchers, and media with aggregated statistics and insights across global industries and topics.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Headquarters: Hamburg, Germany

Founded: 2007

Website LinkedIn

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Statista

2 days ago

Data & Analytics Engineer (m/f/d)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: Hamburg, Berlin

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Design, implement, and maintain Python backend services for the data access and distribution layer.
•Build and operate automated build, test, and deployment pipelines using CI/CD and GitOps on AWS and Kubernetes.
•Design and maintain data models and schemas (Avro, SQL), publishing them to downstream consumers via Kafka and a schema registry.
•Build access-layer data models in analytics environments (e.g., Snowflake) so applications can work with data via API.
•Coordinate between Data and Tech divisions to align priorities, schemas, and timelines across upstream and downstream teams.

Pay and Benefits

Perks:Hybrid WorkHealth InsuranceGym Membership

Key Requirements

•3+ years of experience in analytics engineering, data engineering, or a related role.
•Strong SQL skills and experience with 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.
•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).

Experience:3+ yearsData engineeringAnalytics engineering

Skills:CommunicationAttention to detailQuality-focusedProblem-solvingAnalytical mindset

Languages:EnglishGerman

Tech Stack:PythonCI/CDGitOpsAWSKubernetesAvroSQLKafkaSchema registryProtobufJSON SchemaSnowflakeBigQueryRedshiftDbtClaude CodeAPI

Company Brief

Statista

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Headquarters: Hamburg, Germany

Founded: 2007

Website LinkedIn