Posted 3w ago

Data Engineer / Data Modeler

@ Essnova Solutions
United States
RemoteFull Time
Responsibilities:designing databases, building pipelines, collaborating stakeholders
Requirements Summary:Bachelor's in CS/DS, 5+ yrs data engineering/DBA/architecture, SQL, Python/R, cloud (Azure/AWS), FedRAMP, PowerShell, data modeling, gov’t stakeholders.
Technical Tools Mentioned:PowerShell, Python, R, Git, Azure, AWS, Azure Data Factory, Azure SQL, Azure Blob Storage, Azure Functions, PostgreSQL, SQL Server, Oracle
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Job Description

Essnova Solutions, Inc. is an SBA 8(a) and HUBZone-certified small business delivering technology and professional services to government clients, with a focus on healthcare, geospatial, and environmental solutions. As a Data Engineer / Data Modeler, you will play a pivotal role in designing and maintaining robust data architectures that enable large-scale analytics and support mission-critical government programs. You will collaborate closely with technical teams, security experts, and stakeholders to ensure data solutions are secure, scalable, and compliant with federal standards.

Key responsibilities include:

  • Designing and maintaining scalable database architectures for analytical workloads, ensuring optimal performance through indexing, partitioning, caching, and query tuning.
  • Developing, automating, and maintaining data ingestion, transformation, validation, and loading pipelines to support high-quality data flows.
  • Building reusable data connection modules and backend infrastructure components to streamline data operations and support future scalability.
  • Supporting data preprocessing, normalization, and rigorous data quality validation processes.
  • Contributing to cloud migration planning, governance, and evaluation of cloud solutions for security, compliance, interoperability, and performance.
  • Producing comprehensive data models, architecture diagrams, flowcharts, and technical documentation for internal and external stakeholders.
  • Utilizing PowerShell scripting and automation to enhance data engineering workflows and system integration.
  • Collaborating with technical, security, and stakeholder teams throughout the project lifecycle to deliver high-impact data solutions.