Senior Systems Engineer, UDS Data Management - East

We are looking for a Senior Systems Engineer to provide pre-sales technical support to our field sales teams, helping to define the overall Dell Technologies solution for our customers. The role involves building and leading relationships with highly sophisticated customer accounts, conducting customer needs analysis, and preparing detailed product specifications. The successful candidate will have a strong understanding of data warehousing, data lakes/lakehouse, and ETL/ELT concepts, as well as hands-on experience with major cloud data platforms.

Requirements

• Hands-on experience with at least one major cloud data platform (e.g., Snowflake, Databricks, BigQuery, Redshift, Cloudera, Synapse, or similar).
• Strong understanding of data warehousing, data lakes/lakehouse, and ETL/ELT concepts (staging, modeling, performance tuning, cost/perf tradeoffs).
• Data engineering and integration including unstructured data processing (PDFs, logs, images, text) and transformation into structured/vectorized formats
• Strong SQL skills for analytical queries, performance tuning, and data modeling (star/snowflake schemas, dimensional modeling, partitioning, clustering).
• Unstructured data & AI/RAG: Understanding of vector databases (e.g., Elasticsearch, Milvus, pgvector), embedding models, and RAG architectures. Familiarity with document processing pipelines, chunking strategies, and semantic search patterns.
• Familiarity with data pipeline and orchestration tools (e.g., Airflow, dbt, Spark, Kafka, cloud-native ETL tools) and batch vs. streaming patterns.
• Understanding of data governance (catalog, lineage, security, RBAC, masking, compliance requirements like GDPR/CCPA).
• Analytics, BI, and data science
• Ability to design and explain analytics solutions end-to-end: from raw data to dashboards and predictive models.
• Working knowledge of BI tools (e.g., Tableau, Power BI, Looker, Qlik) and how to connect, model, and optimize for self-service analytics.
• Familiarity with data science and ML workflows (feature engineering, experimentation, model training/deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g., scikit-learn, MLflow, TensorFlow/PyTorch, LangChain, LlamaIndex at a conceptual level).
• 5+ years in a customer-facing technical role such as Sales Engineer, Solutions Architect, Data Engineer, Analytics Consultant, or Data Scientist with strong commercial exposure.
• Proven experience architecting and delivering data management, analytics, or data science solutions in one or more of the following areas:
• Cloud data warehouse or lakehouse migrations
• Enterprise BI modernization/self-service analytics
• GenAI and RAG implementations for enterprise knowledge management, intelligent document processing, or customer-facing AI applications
• Real-time or streaming analytics
• Advanced analytics / data science enablement
• Hands-on experience with at least one major public cloud (AWS, Azure, or GCP) and one or more leading data platforms (e.g., Snowflake, Databricks, Cloudera, BigQuery, Redshift, Synapse)

Benefits

• Health benefits
• Dental benefits
• Vision benefits
• 401(k) matching
• Paid time off
• Relocation assistance
• Generous parental leave