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

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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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:00 min

Separating dataset creation from low-level software implementation steps

Jan Zawadzki · World Congress 2022

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Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

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Integrating an assistant application with Jira software

Felix Augenstein · LIVE

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Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

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Scaling global network engineering through DevOps culture

Stuart Clark · LIVE

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Balancing data science skillings alongside systems engineering rigor

Nico Schmidt · LIVE

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