V.L.S. Systems, Inc

V.L.S. Systems, Inc

1099/W2 Role || Senior Snowflake Data Engineer Modern Data Platforms & AI Exposure || Portland, OR-Onsite

Portland, Oregon, USA · Senior · Contract

Sponsorship not specifiedDetected 36 days ago
PythonSQLSnowflakeAWSAzuredbtData EngineeringData ScienceLLMsRAGCommunication

About the role

  • Strong expertise in SQL and Python programming.

Responsibilities

  • Design, develop, and maintain scalable enterprise data pipelines and modern cloud-based data platforms.
  • Build robust ETL/ELT workflows for ingesting and transforming data from APIs, databases, flat files, and streaming sources.
  • Develop and optimize Snowflake-based solutions including stored procedures, tasks, streams, dynamic tables, Snowpark, and performance tuning.
  • Implement enterprise-scale transformation frameworks using dbt Core and dbt Cloud.
  • Design and maintain scalable and maintainable data models supporting business intelligence, analytics, and operational reporting.
  • Develop API-based integrations and data services for enterprise applications and downstream systems.
  • Collaborate with cross-functional teams including architects, analysts, business stakeholders, and AI/data science teams to deliver enterprise data solutions.
  • Support AI/LLM-enabled initiatives by enabling structured, scalable, and vector-ready data pipelines.
  • Drive technical ownership of data pipelines and platform reliability across development, deployment, and production support activities.

Nice to have

  • Openflow exposure Azure cloud understanding AWS concepts understanding Snowflake Cortex / Snowflake Intelligence exposure AI / LLM / chatbot / RAG / MCP / Agent concepts exposure
  • Work with ETL/ELT tools such as Matillion, Informatica, and Openflow (nice to have).
  • Ensure data quality, governance, scalability, observability, operational reliability, and cost optimization across the data platform.
  • Proactively monitor, troubleshoot, and resolve data pipeline and platform issues in production environments.
  • Participate in architecture discussions and contribute to modern data engineering best practices and standards.
  • Required Skills & Qualifications 8 10 years of experience in Data Engineering, Data Warehousing, or related roles.
  • Strong understanding of enterprise data warehousing concepts, dimensional modeling, and scalable data architecture.
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