Data Manager
Spectraforce
Floriston, CA, United States
8 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Agile Methodology
Artificial Intelligence
Amazon Web Services
JIRA
Microsoft Azure
Information Systems
Information Engineering
Data Governance
Data Integration
Extract Transform Load (ETL)
Data Warehousing
DevOps
+12 more
Meta-Data Management
Scrum Methodology
Cloud Services
DataOps
SQL Databases
Enterprise Data Management
Snowflake
Information Technology
Data Lineage
Data Analytics
Data Management
Data Pipelines
Requirements
- 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
- Data Engineering and Data Management solutions
- Proven success managing cross-functional technical teams.
- Experience working within Agile and Waterfall delivery frameworks., * 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, * PMP, PgMP, Scrum Master, SAFe Agilist, or equivalent certification.
- Experience with enterprise utility, energy, healthcare, financial services, or 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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Prepare application
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