Sr. Data Engineer with Security Clearance Job at L2NL, LLC, Tysons Corner, VA

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  • L2NL, LLC
  • Tysons Corner, VA

Job Description

As Sr. Data Engineer you’ll work with a cross-functional team to help design and ingest data from different Object Management Systems that support mission operations for our classified customer
• Work with AI team members to operationalize data pipelines and ML tasks.
• Provide day-to-day support of deploying Python-native ML pipelines and perform data engineering tasks to enable AI/ML capabilities.
• Present results to a diverse audience in presentation or report form.
• Support architectural leadership, technical support, and advisement services to ensure identity management system technologies are integrated and meeting the appropriate security requirements.
• Support leadership who engage with senior level executives at a public facing Federal agency and provide subject matter expertise in security architecture and other key domain areas. What we’re looking for:
• Minimum 7 years’ experience
• Bachelor's Degree in Computer Science, Information Technology Management or Engineering, or other comparable degree or experience
• Active TS/SCI + CI Poly
• 5+ years of experience in Data/ML engineering
• Strong Experience with ETL, data labeling, and data preparation
• 5+ years experience with one or more of the following technologies: Cloudera, DataBricks, Snowflake, NiFi, Python, SQL, Kafka
• Strong experience designing, developing, and deploying data solutions in classified AWS cloud environments up to IL6+
• Strong experience designing, implementing, and maintaining data architecture and services to be used for AI/ML. Additionally, operationalizing and maintaining AI/ML models in production.
• Strong communication skills, ability to communicate technical concepts in both layman and technical terms to technical and non-technical stakeholders The salary range for this position is determined based on qualifications, skills, and relevant experience. The final salary offered will be determined based on several factors.

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