Senior Data Engineer

KION Group

Senior Data Engineer developing self-service enterprise scale data platforms using microservices at Dematic. Collaborating on architecture, design, and development of key data platform components.

Posted 6/25/2026full-timeAtlanta • Missouri • 🇺🇸 United StatesSenior💰 $133,125 - $204,125 per yearWebsite

Tech Stack

Tools & technologies

AirflowAzureBigQueryCloudDockerETLGoogle Cloud PlatformKubernetesMicroservicesPythonSparkSQL

About the role

Key responsibilities & impact

As a senior data engineer, you will be responsible for ideation, architecture, design and development of our key data platform components
Create and maintain essential data platform SDKs and libraries, adhering to industry best practices
Design and develop connector frameworks and modern connectors to source data from disparate systems both on-prem and cloud
Design and optimize data storage, processing, and querying performance for large-scale datasets using industry best practices while keeping costs in check
Design and develop data quality frameworks and processes to ensure the accuracy and reliability of data
Collaborate with data scientists, analysts, and cross functional teams to design data models, database schemas and data storage solutions
Proactively identify and contribute towards platform resiliency
Design and develop observability and data governance frameworks and practices
Stay up to date with the latest data on engineering trends, technologies, and best practices
Drive the deployment and release cycles, ensuring a robust and scalable platform
Partner with AI enablement teams across the organization as well as KION IT Cloud Infrastructure, AI Platform, and security teams to ensure AI/ML capabilities align with IT framework and guidelines within KION
Partner with Business Transformation Data Management teams to align on master data

Requirements

What you’ll need

5+ years of proven experience in modern cloud data engineering and software engineering
Proven ability to build end-to-end data platforms and data services (beyond ETL)
Strong cloud experience, preferably GCP; Azure (ADLS) and Databricks are strong pluses
Hands-on experience with Databricks (Delta Lake, Spark, ML/ETL workflows)
Experience working in multi-cloud environments (GCP / Azure)
Proficiency with platforms such as BigQuery, Dataflow, Dataform, Cloud Run, DBT, Dataproc, SQL, Python, Airflow, Pub/Sub, and equivalent Azure tooling such as ADLS, Azure Functions, and Databricks
Experience with microservices architectures (Kubernetes, Docker)
Deep experience with batch and streaming data infrastructures
Strong hands-on experience with metadata management, data catalogs, data lineage, data quality, and data observability frameworks
Strong understanding of data modeling, data architecture, and data governance
Solid experience with DataOps, CI/CD, and test automation
Excellent experience with observability tooling
Experience building data platforms supporting AI use cases and machine learning
Production level experience with universal semantic layers
Production level experience with implementing either 3rd party or open-source metadata management platforms
Production level experience with data platform resiliency
Experience building large-scale data platforms on Azure, including Azure Data Lake and Databricks

Benefits

Comp & perks

Career Development
Competitive Compensation and Benefits
Pay Transparency
Global Opportunities

ATS Keywords

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Hard Skills & Tools

data engineeringcloud data engineeringsoftware engineeringdata platformsdata servicesdata modelingdata architecturedata governancedata qualitydata observability

Soft Skills

collaborationproblem-solvingcommunicationproactive identificationorganizational skills