Staff Data Engineer

Laurel Inc

$120K — $150K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in backend development with a strong focus on Python for AI/ML applications.
  • Proven expertise in data pipeline architecture and modern event-driven data systems.
  • Experience with container orchestration tools like Kubernetes and CI/CD pipelines.
  • Familiarity with AWS services and deployment best practices.
  • Solid understanding of database management with PostgreSQL and MongoDB.

Responsibilities

  • Design and evolve a large-scale data platform architecture for global use.
  • Develop large-scale data pipelines that can handle millions of events daily.
  • Define and implement best practices for data handling processes.
  • Mentor team members on big data best practices and modern techniques.
  • Work on Django-based API services to enhance AI serving capabilities.
  • Optimize existing data management systems including Airflow and MongoDB.
  • Implement and maintain streaming data infrastructure utilizing technologies like Kafka.

Benefits

  • Remote work flexibility with a preference for candidates near major hubs.
  • Comprehensive medical, dental, and vision coverage with premiums covered.
  • 401(k) plan with company matching and other financial benefits.
  • Wellness, commuter, and flexible spending account stipends.
  • Supportive workplace culture that prioritizes health and work-life balance.
Full Job Description
About the Role

Laurel's infrastructure, data, and security team is lovingly named the Time Owls. We make Laurel's infrastructure more reliable, secure, and easy to use. Our team builds and maintains the tools, platforms, and automation that enable engineers across the company to work with AWS, Kubernetes, and other services easily and safely. We contribute to all applications in the company and act as both best-practice advocates and policy enforcers.

This role sits at the intersection of infrastructure and AI. You'll work closely with our AI engineers and data scientists, focusing on making their work fast, efficient, scalable, and secure. You'll own data pipelines, model-serving infrastructure, and the systems that move data reliably through our platform - from ingestion through to production inference.

If you are more interested in general infrastructure than data and ML systems, please check out our Platform Engineering role.

Responsibilities
  • Design and evolve Laurel's global large scale data platform architecture
  • Design and operate large-scale data pipelines processing millions of events per day.
  • Define best practices for data ingestion, transformation, processing, and storage.
  • Mentor and help grow team and our knowledge of big data best practices along with encouraging modern techniques
  • Work on Python API services (Django) to improve the serving of our AI infrastructure.
  • Build, improve, and maintain Airflow DAGs, and optimize MongoDB and PostgreSQL usage for data workloads.
  • Design and operate streaming data infrastructure, including migrations to modern event-driven architectures (e.g., Kafka).
  • Work on internal OLAP and DataLake systems (e.g. Clickhouse)
  • Develop and manage Kubernetes, Docker, and compute infrastructure for all of engineering.
  • Improve continuous integration, continuous deployment, and other automation.
  • Write backend code to help teams deliver functionality when there are deadlines or resource constraints.
  • Attend quarterly offsites (required travel), team standups, and other company meetings.
  • Raise the bar for engineering quality and advocate for best practices across the organization.


What We're Looking For

The following are our non-negotiables for candidates.
  • Strong Python skills with experience building and deploying APIs to support AI/ML teams in delivering models to end users.
  • Experience with Airflow, Kubernetes, and AWS.
  • Experience with machine learning infrastructure and large language models.
  • Development experience with Terraform.
  • Experience working in startup environments.
  • Experience participating in a regular engineering on-call rotation.
  • Experience with PostgreSQL and MongoDB.
  • Experience with OLAP systems (Snowflake, Clickhouse, etc)
  • Experience with AI Specific Databases (Vector Databases for example)
  • Experience with event streaming platforms (e.g., Kafka, SQS).


Nice to Haves

The following would help make this role a perfect fit.
  • Experience with Argo (Workflows and/or CD).
  • Experience with cdk8s.
  • Experience with OpenTelemetry and observability platforms (e.g., Observe, Datadog).
  • Experience with Spacelift.
  • Experience with CircleCI and/or GitHub Actions.
  • Experience with TypeScript and Go.
Flexibility and Logistics
  • Location: This role is remote, with preference for candidates based near our hubs in San Francisco, Los Angeles, or New York City.
  • Additional Benefits: Comprehensive medical/dental/vision coverage with covered premiums, 401(k), and additional benefits including wellness, commuter, and FSA stipends.
  • Visa Sponsorship: Unfortunately, we are unable to sponsor visas at this time.
  • What happens if my kid or I are sick on a workday? Take all the time you need! We'll cover for you. And send you some soup.

We encourage diverse perspectives and rigorous thinkers who aren't afraid to challenge the status quo. If you think you'd be a good fit for this role, we encourage you to apply, even if you don't perfectly match all the bullet points in the job description. At Laurel, we strive to create an inclusive culture that encourages people from all walks of life to bring their unique, diverse perspectives to work. Every day, we aim to build an environment that empowers us all to do the best work of our careers, and we can't wait to show you what we have to offer!

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