MLOps & Data Engineer II

• →Bachelor’s degree in Computer Science, Data Engineering, or a related field.
• → 2+ years of experience in data engineering or a related role.
• → Higher level relevant degree may substitute for experience.
• → Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 6 years of related experience is required. 
• → Proficiency in SQL and experience with ETL/orchestration tools such as Airflow, dbt, or Prefect.
• → Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• → Strong problem-solving and analytical skills.
• → Working SQL knowledge and experience working with relational databases.
• → Experience with AWS cloud services: S3, Redshift, Glue.
• → Experience building data pipelines, architectures, and data sets.
• → Experience performing root cause analysis on data to answer specific business questions or issues.
• → Strong Python skills, with experience in data engineering frameworks such as Spark, dbt, Airflow, or Prefect.
• → Operational responsibilities (schedules, monitoring, logging, alerting, error handling, etc.)
• →Exposure to ML lifecycle tools such as MLflow, Weights & Biases, or Kubeflow.

•  Experience building data pipelines, architectures, and data sets. 
•  Experience performing root cause analysis on data to answer specific business questions or issues. 
•  Experience with AWS cloud services (e.g., S3, EC2, RDS, Redshift, Glue, Lambda, Step Functions, Athena, CloudWatch, ECS, IAM). 
•  Experience with object-oriented scripting languages and frameworks (e.g., Python, Java). 
•  Familiarity with source system integration patterns (e.g., SQL, APIs). 
•  Exposure to operational responsibilities (schedules, monitoring, logging, alerting, error handling, etc.). 
•  Basic understanding of Master Data Management (MDM) concepts and exposure to MDM solutions. 
•  Familiarity with DevOps practices and tools, with some hands-on experience in a CI/CD environment. 
•  Experience with big data technologies (e.g., Hadoop, Spark). 
•  Certifications in data engineering or related fields.

•  Ability to work on a computer for extended periods.
•  Frequent communication with team members and stakeholders.
•  Ability to work in an office or hybrid environment.
•  Occasional travel may be required.
•  Must be able to lift up to 10 lbs occasionally.
•  Ability to ensure data engineering practices adhere to industry-specific regulations and security standards (e.g., ITAR, DFARS, NIST), safeguarding sensitive data throughout the data lifecycle.
•  Experience with ML lifecycle tools such as MLflow, Weights & Biases, or Kubeflow
• Familiarity with feature store platforms (Feast, Tecton, Hopsworks)
• Experience with graph databases (Neo4j, Amazon Neptune) supporting knowledge graphs or entity resolution
• Familiarity with vector databases or retrieval-augmented generation (RAG) pipelines (Pinecone, Weaviate, pgvector)
• Experience with Kubernetes for deploying data or ML workloads
• Familiarity with data observability tools (Monte Carlo, Great Expectations)

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We’re known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation’s most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team!

SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.