Altruist
Staff Back End Engineer
San Francisco, CA · Staff+
Sponsorship not specified$203k-$275kDetected 149 days ago
JavaSpringDistributed SystemsPostgreSQLAWSKubernetesData AnalysisData EngineeringCommunicationCollaborationProblem Solving
About the role
- Altruist is in the midst of an exceptional growth phase and we're excited to hire Staff Back End Engineers to join our growing Engineering organization.
- We have multiple teams hiring for high impact & high visibility projects.
- Our recruitment team will work with you to match you to the right opportunity to help you grow your career at Altruist.
Responsibilities
- Act as a leader and steward of engineering best practices, helping to mentor other engineers and develop impactful solutions.
- Focus on building and scaling services and user facing web applications
- Build customer centric scalable and performant applications and features
- Develop and maintain scalable data pipelines and ELT processes
- Build new data integrations based on established requirements
- Perform data analysis to investigate and resolve data issues
- 6+ years of software engineering experience building precise and scalable distributed systems with best engineering practices
- Our offices are intentionally designed for comfort, collaboration, and productivity.
Requirements
- You possess a strong knowledge base, the ability to discover the unknown, and are open to differing perspectives.
- Ideally looking for a B.A. / B.S. degree in relevant fields such as Computer Science or similar Engineering/Mathematics degrees
Compensation
- Professional growth and development opportunities including an employee mobility program and an annual L&D budget allocation for each employee.
Benefits
- Competitive pay and equity for eligible positions.
- Premium healthcare, dental, and vision insurance plans (HMO and PPO).
- 401k savings plan with a 4% match and immediate vesting.
- 16 week paid parental leave after one year of employment.
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This listing is sourced directly from Altruist's careers page and normalized into a canonical job model.