Solutions Engineer
$100 - $110 per hourTheCorporate LLC
Solutions Engineer IV
Location: Remote within the U.S. (approximately 90% remote; local candidates preferred)
Duration: October 26, 2026 to December 31, 2026
About the Role
We're seeking a Solutions Engineer to lead enterprise data platform implementations and manage complex, data-driven technology projects. You'll guide cross-functional technical teams across data engineering, data governance, and data quality initiatives, delivering with both Agile and Waterfall frameworks.
Required Qualifications
Education
- Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related field.
- Master's degree preferred.
Experience
- 8+ years of experience managing complex technology or data-driven projects.
- 5+ years leading enterprise data platform implementations.
- Experience delivering projects involving Snowflake, Palantir Foundry, Ataccama, and data engineering and data management solutions.
- Proven success managing cross-functional technical teams.
- Experience working within Agile and Waterfall delivery frameworks.
Required Technical Skills
Data Platforms
- Palantir Foundry
- Snowflake
- Ataccama
- Cloud data platforms (AWS, Azure, or GCP)
Data Engineering
- ETL/ELT development
- Data warehouse and lakehouse architectures
- Data pipeline orchestration
- Data integration frameworks
- SQL and data modeling concepts
Data Governance & Quality
- Master Data Management (MDM)
- Data quality management
- Metadata management
- Data governance frameworks
- Data lineage and cataloging
Project Management
- Agile/Scrum
- Jira, Azure DevOps, or similar tools
- Program planning and governance
- Budget and resource management
- Risk and dependency management
Preferred Qualifications
- PMP, PgMP, Scrum Master, SAFe Agilist, or equivalent certification.
- Experience in utility, energy, healthcare, financial services, or other large-scale regulated industries.
- Knowledge of data privacy and compliance frameworks.
- Experience with DevOps and DataOps practices.
- Familiarity with AI/ML enablement through enterprise data platforms.
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