Smart IT Frame LLC
Cloud Data Engineer
Richmond, Virginia · Senior
Stay score
odds of building a lasting career here
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Third-party placement is common here
Files H-1B transfers
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- We are seeking a Cloud Data Engineer with strong experience and cloud-based data platforms.
Responsibilities
- Design and develop scalable data solutions on Snowflake.
- Build and maintain data pipelines and ETL/ELT processes.
- Optimize data warehouse performance and cost efficiency.
- Collaborate with business and technology teams to deliver data-driven solutions.
Nice to have
- Snowflake or Cloud certifications.
- Experience with real-time data processing and big data technologies.
- Prior experience in banking, financial services, or fintech environments.
Skills
- 5+ years of Data Engineering experience.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Proficiency in SQL and Python.
- Knowledge of data modeling, data warehousing, and performance tuning.
- Experience with CI/CD, Git, and Agile methodologies.
- Strong analytical and problem-solving skills.
- Cloud Data Engineer
- Richmond /Mclean VA (Onsite)
Company info
- Job Title: Cloud Data Engineer Location: Richmond /Mclean VA (Onsite) Contract Job Description: We are seeking a Cloud Data Engineer with strong experience and cloud-based data platforms.
This listing is sourced directly from Smart IT Frame LLC's careers page and normalized into a canonical job model.