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      Senior Systems Engineer, UDS Data Management - East

      Dell CareersFall River, MA

      697 Python jobs in East Providence, RI

      New, Posted 21 hours ago
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      Senior Systems Engineer, UDS Data Management - East

      Dell

      Fall River, MA 02722

      Remote

      • Proven experience architecting and delivering data management, analytics, or data science solutions in one or more of the following areas:
      • Ability to design and explain analytics solutions end-to-end: from raw data to dashboards and predictive models
      • Skilled at asking the right questions to uncover technical requirements, constraints, and business drivers
      • Competitive positioning
      • Can structure and run POCs with clear success criteria, timelines, and executive readouts to accelerate technical win
      • Strong understanding of data warehousing, data lakes/lakehouse, and ETL/ELT concepts (staging, modeling, performance tuning, cost/perf tradeoffs)
      • Comfortable presenting to large groups and senior stakeholders (CIO/CDO, Heads of Data/Analytics)
      • Enterprise BI modernization/self-service analytics
      • Advanced analytics / data science enablement
      • Unstructured data & AI/RAG: Understanding of vector databases (e.g., Elasticsearch, Milvus, pgvector), embedding models, and RAG architectures
      • 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
      • Strong SQL skills for analytical queries, performance tuning, and data modeling (star/snowflake schemas, dimensional modeling, partitioning, clustering)
      • Excellent at translating complex technical topics into clear, business-oriented narratives for both technical and non-technical audiences
      • Storytelling & communication
      • Cloud data warehouse or lakehouse migrations
      • Consulting Skills
      • Demo & POC excellence
      • GenAI and RAG implementations for enterprise knowledge management, intelligent document processing, or customer-facing AI applications
      • 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)
      • 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)
      • Can translate ambiguous business problems into clear data and analytics use cases
      • Data engineering and integration including unstructured data processing (PDFs, logs, images, text) and transformation into structured/vectorized formats
      • Working knowledge of BI tools (e.g., Tableau, Power BI, Looker, Qlik) and how to connect, model, and optimize for self-service analytics
      • Hands-on experience with at least one major cloud data platform (e.g., Snowflake, Databricks, BigQuery, Redshift, Cloudera, Synapse, or similar)
      • Analytics, BI, and data science
      • Real-time or streaming analytics
      • Familiarity with document processing pipelines, chunking strategies, and semantic search patterns
      • Understands the broader data & AI ecosystem and can articulate differentiation versus other data warehouses, data lake/lakehouse platforms, and analytics tools
      • 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)
      • Able to build and deliver compelling demonstrations that tell a story around customer data and use cases, not just features
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