Altruist

Altruist

Staff Back End Engineer, Trading

San Francisco, CA · Staff+

Sponsorship not specified$203k-$275kDetected 82 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 Trading team.
  • This is a hybrid role, with an expectation of being in the office three days each week out of our Culver City or San Francisco office.

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
  • 8+ 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.

This listing is sourced directly from Altruist's careers page and normalized into a canonical job model.