Data Engineer – Fulfillment & Logistics Data

INTERSPORT Deutschland eG

. Develop and operate scalable data products and ETL/ELT pipelines for fulfillment and logistics processes .

Posted 10/27/2026full-timeRemote • GermanyMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced expertise in Data Engineering, focusing on developing scalable data products and ETL/ELT pipelines. Proficient in SQL, Python, and modern data stack technologies, with a strong emphasis on data quality, governance, and collaboration across cross-functional teams.

Highest-signal resume keywords

Data Engineering ExperienceAdvanced SQL KnowledgePython ProgrammingETL/ELT Pipeline DevelopmentData Quality and Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonETLELTData ModelingData QualityData GovernanceSLA MonitoringPerformance AnalysisData Integration

Soft Skills

Solutions-OrientedStructured ApproachCollaboration

Tools & Technologies

SnowflakeDbtPrefectKafkaAWSPulumiTerraformLookerMetabasePower BI

Industry Keywords

Order Management SystemsFulfillmentLogisticsShipping DataE-CommerceMarketplaceData MeshDomain-Oriented Data ProductsAPIsEvent Streaming Technologies

Tech Stack

Tools & technologies

AWSETLKafkaPythonSnowflakeSQLTerraform

About the role

Key responsibilities & impact

Develop and operate scalable data products and ETL/ELT pipelines for fulfillment and logistics processes
Integrate data from order management systems, marketplaces, shipping carriers, and tracking systems
Model data related to shipping, delivery, returns, refunds, and partner performance
Build the data foundation for SLA monitoring, performance analysis, and dashboards
Provide fulfillment and tracking data to other product areas and digital services such as Customer Service
Integrate event-based data sources, including Kafka
Ensure data quality, governance, and privacy, while continuously improving monitoring and quality checks
Work closely with Product Management, Engineering, and Operations
Own data products from business requirements through production operation
Actively contribute to the Data Engineering practice and help develop shared standards and ways of working

Requirements

What you’ll need

Several years of experience in Data Engineering or a comparable role
Advanced knowledge of SQL and Python, with experience in ETL/ELT and data modeling
Experience integrating operational or transactional systems and APIs
Experience with a modern data stack, ideally including Snowflake, dbt, and Prefect
Experience with Kafka or comparable event and streaming technologies
Knowledge of AWS; ideally also experience with Infrastructure as Code using Pulumi or Terraform
Solid understanding of data quality and Data Governance
Experience collaborating with cross-functional product or engineering teams
Independent, structured, and solutions-oriented approach to work
German at least B2 level and fluent English
Experience with order, fulfillment, logistics, or shipping data (nice to have)
Knowledge of OMS, carrier, or tracking systems and their interfaces (nice to have)
Experience with SLA and performance monitoring or data-driven partner management (nice to have)
Knowledge of Data Mesh and domain-oriented data products (nice to have)
Experience with BI tools such as Looker, Metabase, or Power BI (nice to have)
Experience in an e-commerce, marketplace, or platform environment (nice to have)

Benefits

Comp & perks

Flexible working hours
Remote work options
Professional development opportunities
Employee discounts
A modern data stack featuring Snowflake, dbt, Prefect, Kafka, AWS, and Pulumi
Direct impact on fulfillment efficiency, delivery quality, and partner performance
Close collaboration with Product, Engineering, and Operations
A shared Data Engineering practice with knowledge exchange and clear standards