Overview
On Site
Depends on Experience
Contract - Independent
Contract - W2
Contract - 1 Year(s)
Able to Provide Sponsorship
Skills
Agile
Big Data
Collaboration
Functional Requirements
Communication
Innovation
Data Governance
Optimization
Informatica
Job Details
Role: Data Engineer
Location: Oakland Bay Area -CA (Onsite)
Job Responsibilities
Location: Oakland Bay Area -CA (Onsite)
Job Responsibilities
- Lead Technical Implementation: Drive the design and development of Palantir Foundry solutions; ensure technical excellence from planning through deployment.
- Cross-Platform Expertise: Learn and support Snowflake and Informatica use cases as needed to support data platform integration.
- Performance & Governance: Ensure adherence to best practices in performance tuning, security, and data governance across platforms.
- Team Leadership: Mentor and lead development teams with a hands-on approach, fostering a collaborative and high-performing culture.
- Product Development: Build scalable, high-quality big data products within an agile, innovation-driven environment.
- Technical Feasibility & Architecture: Collaborate with Product Owners and Designers to assess feasibility and define scalable, maintainable architectures.
- Non-Functional Requirements: Define and manage aspects such as scalability, reliability, maintainability, and technical debt.
- Debugging & Optimization: Troubleshoot complex systems and optimize for performance and efficiency.
- Communication & Collaboration:
- Communicate technical concepts clearly to both technical and non-technical stakeholders.
- Work closely with security and external teams to ensure robust, compliant, and efficient solutions.
- Agile Methodology: Follow and advocate for agile software development practices.
- Continuous Learning & Innovation: Stay current with Palantir Foundry capabilities, advocate for best practices, and drive innovation by leveraging new features.
- Data Modeling & Processing: Promote effective data modeling approaches, particularly for integrating event-driven and batch data processing workflows.
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