Senior Data Engineer

At Dematic, we are revolutionizing our data landscape in support of cutting-edge Artificial Intelligence (AI) use cases. We are forming multiple teams that will spearhead the creation of the platform's foundational components. These teams go beyond traditional data ingestion; they are architects of a microservices-driven platform, providing abstractions that empower other teams to seamlessly extend the platform. We are seeking a dynamic and highly skilled Senior Data Engineer who has extensive experience building self-service enterprise scale data platforms with microservices architecture and leading these foundational efforts. This role demands someone who not only possesses a profound understanding of the data engineering landscape but also has experience with software engineering design patterns and microservices frameworks. The ideal candidate will be 100% hands-on, deep in the code and individual contributor who will contribute significantly to platform development and actively shape our data ecosystem. We offer: Career Development Competitive Compensation and Benefits Pay Transparency Global Opportunities Learn More Here: Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. The base pay range for this role is estimated to be $133,125 - $204,125 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge, and skills. Tasks and Qualifications: What You Will do in This Role: 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. What We are Looking for: 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.

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