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Website: dell.com
Dell Inc., formerly Dell Computer Corporation, is an American technology company that develops, sells, repairs, and supports personal computers (PCs), servers, data storage devices, network switches, software, computer peripherals including printers and webcams among other products and services. Dell is based in Round Rock, Texas.
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Dell is hiring a Senior Systems Engineer, UDS Data Management to join our Systems Engineering team in Germany — a customer-facing technical role where modern data and AI strategy meets real business outcomes. About the Role As a Senior Systems Engineer at Dell, you'll work alongside our field sales professionals as the trusted technical authority throughout the sales cycle. Sitting where technology, customer success, and commercial impact converge, you'll architect data and AI solutions, turn intricate requirements into actionable use cases, and craft the proposals that move customers forward on their Data & AI transformation journey. This is a full-time position based in Germany. Key Responsibilities Establish credible, lasting relationships with customers and lead discovery sessions to uncover their objectives, obstacles, and technical priorities. Architect and validate cloud-native solutions for data, analytics, and AI/GenAI/RAG workloads. Produce clear solution designs, proposals, and supporting technical documentation that steer customers through their transformation. Run high-impact demonstrations and proofs of concept that prove value, feasibility, and tangible business results. Translate sophisticated data and AI ideas into plain language for both technical specialists and business leaders. Assess competing data and AI platforms and clearly position how Dell's solutions differentiate. Qualifications Hands-on expertise with major cloud and data platforms (Snowflake, Databricks, BigQuery, Redshift, Synapse, Cloudera) plus at least one of AWS, Azure, or GCP. Solid data architecture and engineering grounding: warehousing, data lakes/lakehouse, SQL, ETL/ELT, star/snowflake modeling, performance tuning, governance, and GDPR/CCPA compliance. Experience building pipelines and handling unstructured data using Airflow, dbt, Spark, and Kafka across batch and streaming, including processing PDFs, logs, images, and text into structured or vectorized formats. Working knowledge of AI/GenAI and RAG fundamentals: vector stores (pgvector, Elasticsearch, Milvus), embeddings, semantic search, chunking, and document processing. Broad BI and analytics fluency (Power BI, Tableau, Looker, Qlik) and end-to-end design from raw data to dashboards. Strong storytelling and presentation skills for senior stakeholders such as CIOs and CDOs, plus proven discovery and PoC capabilities. 5+ years in a customer-facing technical role (Sales Engineer, Solutions Architect, Data Engineer, Analytics Consultant, or Data Scientist) with commercial exposure. Desirable: ML/AI workflow experience (Python, Spark, MLflow,…
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