Staff Data Engineer, Analytics in San Francisco, CA

$100K - $150K(Ladders Estimates)

PagerDuty   •  

San Francisco, CA 94102

Industry: Enterprise Technology


8 - 10 years

Posted 63 days ago

This job is no longer available.

At PagerDuty, we believe that people do their best in a culture that fosters inclusion, innovation, and success. Our values - Champion the Customer, Take the Lead, Run Together, Ack + Own and Bring Yourself - serve as the foundation of our collaborative and dynamic culture. Whether it's conducting a retrospective, participating in our monthly Hackdays, cranking out a new product feature, supporting our two PagerDuty bands, or doing our day to day work, Dutonians live and breathe these five values every day. Together, we solve real customer issues and fulfill our mission of connecting teams to real-time opportunities and elevate work to the outcomes that matter.

Why We Need You

PagerDuty is the leading digital operations management platform for businesses. Our SaaS-based solution empowers over 10,000 small, midsize and enterprise global customers to gain insight and respond to critical disruptions. PagerDuty is trusted by thousands of users every single day, which is why leading digital businesses turn to us for the metrics and measures that define their operational effectiveness and agility.We are extending this idea by investing in Analytics. We believe that we can transform the way digital businesses work, using data to measure and improve digital operations, with a direct link to better business outcomes. As a Staff Data Engineer, you will help define the architecture for the next generation of our data platform and its evolution for the long term. You will be at the forefront of building out this new platform with the support and resources of the larger organization. This platform will be responsible for providing operational insights and guidance to users of PagerDuty on how they can improve their digital operations through the rich set of data we have collected over the last 10+ years. In addition, you will be providing guidance to the engineering team on contributing to this data architecture and enabling them to leverage this platform. At PagerDuty, each of our teams operates in the form of a startup within a startup and that provides every member with the opportunity and autonomy to express all their creativity when breaking new ground in a space that is filled with conventional, non-actionable offerings. This is a truly unique opportunity to work with engineers and product owners across multiple teams with datasets that span many organizations across all industries and sizes.

How You Will Contribute

  • Drive the design and evolution of a data platform that supports not only the Analytics product line but also organization-wide Product development efforts.
  • Collaborate closely with engineers and data scientists across the organization towards the evolution of the data platform.
  • Contribute to the long-term technical vision for PagerDuty's Product data platform including evolution/expansion of event data sources and platform scaling.
  • Design/implement scalable, highly available services to support various aspects of the data platform.
  • Help non-technical audience understand technical requirements.
  • Drive thought leadership and define best practices around data extraction, modeling, consumption, and governance.
  • Provide guidance, technical leadership, and mentoring to other members of the Engineering team.
  • Participate in your team's on-call rotation, triaging and addressing production issues as they arise.

Skills and Attributes

  • You have 8+ years of experience designing and developing customer-facing SaaS applications and data-driven applications.
  • You come with a set of broad and deep tools including: Batch/Stream based processing frameworks such as, but not limited to Spark, Pig, Flink, etc. Data transformation leveraging ecosystem built with Scala, Python, R, etc. Cloud services such as AWS, Azure, and GCP. Datastore technologies (both RDBMS and NoSQL).
  • You have a good understanding of the full web service architecture/technologies (e.g. CDN, request headers, API design, service load balance/routing, disaster recovery).
  • You have 5+ years of experience in building and designing scalable Data pipeline which included making trade-offs between consistency, availability, complexity, etc.
  • Empathetic - you can clearly communicate your thoughts and opinions to others and facilitate these technical discussions to a successful outcome.

Preferred Qualifications

  • Experience with AWS cloud ecosystem.
  • Experience with machine learning and working with data science teams.
  • Contributions to open source projects.
  • Experience building and operating highly scalable, high availability services.
  • You have a strong passion for developing elegant and well-designed frameworks

Valid Through: 2019-9-13