Senior Data Engineer

GLS/NXT

. Collaborate across functions to scale GLS/NXT data infrastructure .

Posted 10/4/2026full-timeBerlin • GermanySeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and scaling data engineering pipelines, integrating diverse data sources, and ensuring data quality for analytics and reporting. Proficient in utilizing cloud platforms and orchestration tools to support data infrastructure and applications.

Highest-signal resume keywords

Data Engineering Pipeline DesignApache AirflowPythonAWSGoogle BigQuery

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData ModelingSQLDBTSchema DesignData Quality ManagementTesting StrategiesWorkflow OrchestrationIncremental StrategiesQuery Optimization

Soft Skills

Strong English CommunicationHighly OrganizedProject ManagementTask PrioritizationCollaboration

Tools & Technologies

GCPSnowflakeLookerLookMLCI/CD Pipelines

Industry Keywords

Data InfrastructureData WarehousingAnalytics PlatformCross-Functional ProjectsAgile Methodologies

Tech Stack

Tools & technologies

AirflowApacheAWSBigQueryGoogle Cloud PlatformPythonSQLGo

About the role

Key responsibilities & impact

Collaborate across functions to scale GLS/NXT data infrastructure
Contribute to the roadmap and development of GLS/NXT data products
Design, build, monitor, and scale data pipelines for data warehousing
Integrate various data sources and destinations
Develop data models and schemas supporting analytical requirements
Work with engineering teams to resolve architecture and infrastructure challenges
Design effective technical solutions
Participate in cross-functional projects supporting data applications and reporting
Address data quality issues and implement best practices
Create and maintain comprehensive systems documentation
Ensure the reliability and integrity of the data infrastructure and analytics platform
Design and implement testing strategies
Proactively identify data quality issues
Enable accurate, trustworthy data for analytics and reporting

Requirements

What you’ll need

Bachelor's degree in Computer Science or a related engineering field
5+ years of proven experience in data engineering roles
Expertise in designing, building, monitoring, and scaling data engineering pipelines
Hands-on experience with workflow orchestration tools such as Apache Airflow
Proficient in Python and Go
Extensive hands-on experience with AWS and GCP
Proficient with Google BigQuery and Snowflake
Proficient in SQL for diverse data sources
Experience with DBT for data modeling, schema design, incremental strategies, and query optimization
Looker and LookML expertise
Software development operations management experience, including CI/CD pipelines and agile methodologies
Strong English communication skills
Highly organized with the ability to prioritize tasks and manage projects aligned to business goals
Skilled at setting clear priorities to drive project success

Benefits

Comp & perks

Hybrid working mode with a tailored remote policy
Personal budget of 1.000€ for learning and development initiatives
Great office space in Berlin Mitte with top-tier equipment
Transparent and competitive compensation
Clear bonus system enabling participation in your and the team’s performance
Monthly team cooking
Regular events and offsites
30 days of yearly holiday
Rewards for the recommendation of additional team members