Principal Software Development Engineer - Developer Productivity & Insights
Expedia, Inc., Austin, TX, United States
Why Join Us?
To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated, and when one of us wins, we all win.
We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, a flexible work model, and career development resources to fuel our employees’ passion for travel and ensure a rewarding career journey.
Introduction to Team
Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools that deliver high‑quality experiences for travelers, partners, and employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
The Principal Software Development Engineer role is part of the Developer Experience team at the intersection of DevEx, data, and business strategy. The Developer Experience team provides tools, platforms, metrics, and enablement programs that reduce friction for engineers, streamline software delivery workflows, and improve developer satisfaction and productivity across Expedia Group.
In this role, you will focus on Developer Productivity & Insights—defining how we measure and understand engineering effectiveness, partnering with platform and product teams to synthesize signals across SDLC systems and translating those insights into clear narratives and recommendations for senior engineering leadership up to the CTO office. Rather than owning a single platform, you will drive change through influence: shaping our metrics strategy, evaluating how AI is changing developer workflows, and turning data into better tools, workflows, and outcomes for engineers across Expedia Group.
In this role, you will:
Define and evolve the
end-to-end strategy, metrics framework, and data model for Developer Productivity & Insights , ensuring it aligns with industry best practices.
Design and maintain
robust data pipelines, schemas, and dashboards
that integrate SDLC signals (Git, CI/CD, Jira, incident/change data, AI tooling) into a coherent, trusted view of engineering effectiveness.
Lead
deep analytical investigations
into developer productivity, flow, and quality, turning noisy telemetry into clear narratives, causal hypotheses, and concrete recommendations for senior engineering leadership.
Partner with DevEx, Platform, and product teams to
experiment with changes to tools, workflows, and guardrails , measuring impact (before/after) and operationalizing practices that demonstrably improve outcomes.
Define, validate, and iterate
productivity “north star” and leading indicators
(e.g., repo readiness, power‑user profiles, AI usage depth) and prune or simplify metrics that don’t drive decisions.
Act as the
technical owner for engineering-wide insights tooling
(e.g., LinearB/SEI platforms, internal analytics services), setting standards for data quality, instrumentation, and observability.
Collaborate closely with the CTO office and senior engineering leaders to
shape AI‑era productivity strategy , including how AI‑assistive and agentic workflows are measured, governed, and reported.
Mentor engineers and technical leaders on
using data to run better teams —from instrumenting services and repos to interpreting metrics, designing experiments, and avoiding misuse of vanity metrics.
Minimum Qualifications:
Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
10+ years of software development experience delivering and operating large‑scale, distributed systems or platforms, including ownership of multiple services or a significant technical domain.
Experience leading developer relations or technical evangelism efforts at scale in enterprise or platform environments.
Proven expertise in designing and implementing service architectures, including system design (LLD), API design, and data modeling, with strong proficiency in at least one modern programming language and associated ecosystems.
Demonstrated experience driving engineering best practices (testing, observability, performance, reliability, security) and leading complex initiatives from design through production operation.
Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real‑world products, with the ability to safely integrate and operate AI/ML‑enabled components within existing services.
Preferred Qualifications:
Experience with developer productivity, platform engineering, or horizontal core services teams, including ownership of CI/CD tooling and deploying code at scale.
Deep, hands‑on understanding of the
software development lifecycle (SDLC) , CI/CD pipelines, and getting code safely to production in large, distributed systems.
Strong
data science and analytics background ; skilled at combining multiple data sources, applying analytical techniques, and turning findings into actionable insights for engineering leadership.
Hands‑on experience
measuring developer productivity
using frameworks such as DORA or SPACE.
Demonstrated
executive presence
with a track record of translating complex technical and data concepts into clear narratives and data stories for senior engineering and CTO‑level leaders.
Practical experience with
AI developer tools
(e.g., Claude, GitHub Copilot, Cursor, Codex, Kiro), including evaluating adoption, usage depth, and impact on developer workflows and outcomes, with concrete examples of using AI in day‑to‑day work.
Experience building
analytics and reporting that answer executive questions
about AI adoption, productivity impact, and quality/reliability outcomes (e.g., monitoring and interpreting change failure rate and related metrics).
Understanding of causal inference methods to measure the impact of tooling and workflow changes and proficiency in SQL and modern data platform tooling (e.g., Spark, Databricks) for building and maintaining analytical pipelines at scale.
Pay ranges vary by location and may be modified in the future. For example, the cash range in Chicago is $214,500 to $300,000, with potential to increase to $343,000 based on performance. For Seattle, the range is $231,000 to $323,500, with potential to increase to $369,500. For Austin, the range is $231,000 to $323,500, with potential to increase to $369,500. For San Jose, the range is $249,000 to $348,500, with potential to increase to $398,500.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E‑Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s I‑9 to confirm work authorization.
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To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated, and when one of us wins, we all win.
We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, a flexible work model, and career development resources to fuel our employees’ passion for travel and ensure a rewarding career journey.
Introduction to Team
Our Technology Team partners with teams across Expedia Group to create innovative products, services, and tools that deliver high‑quality experiences for travelers, partners, and employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences that drive loyalty and traveler satisfaction.
The Principal Software Development Engineer role is part of the Developer Experience team at the intersection of DevEx, data, and business strategy. The Developer Experience team provides tools, platforms, metrics, and enablement programs that reduce friction for engineers, streamline software delivery workflows, and improve developer satisfaction and productivity across Expedia Group.
In this role, you will focus on Developer Productivity & Insights—defining how we measure and understand engineering effectiveness, partnering with platform and product teams to synthesize signals across SDLC systems and translating those insights into clear narratives and recommendations for senior engineering leadership up to the CTO office. Rather than owning a single platform, you will drive change through influence: shaping our metrics strategy, evaluating how AI is changing developer workflows, and turning data into better tools, workflows, and outcomes for engineers across Expedia Group.
In this role, you will:
Define and evolve the
end-to-end strategy, metrics framework, and data model for Developer Productivity & Insights , ensuring it aligns with industry best practices.
Design and maintain
robust data pipelines, schemas, and dashboards
that integrate SDLC signals (Git, CI/CD, Jira, incident/change data, AI tooling) into a coherent, trusted view of engineering effectiveness.
Lead
deep analytical investigations
into developer productivity, flow, and quality, turning noisy telemetry into clear narratives, causal hypotheses, and concrete recommendations for senior engineering leadership.
Partner with DevEx, Platform, and product teams to
experiment with changes to tools, workflows, and guardrails , measuring impact (before/after) and operationalizing practices that demonstrably improve outcomes.
Define, validate, and iterate
productivity “north star” and leading indicators
(e.g., repo readiness, power‑user profiles, AI usage depth) and prune or simplify metrics that don’t drive decisions.
Act as the
technical owner for engineering-wide insights tooling
(e.g., LinearB/SEI platforms, internal analytics services), setting standards for data quality, instrumentation, and observability.
Collaborate closely with the CTO office and senior engineering leaders to
shape AI‑era productivity strategy , including how AI‑assistive and agentic workflows are measured, governed, and reported.
Mentor engineers and technical leaders on
using data to run better teams —from instrumenting services and repos to interpreting metrics, designing experiments, and avoiding misuse of vanity metrics.
Minimum Qualifications:
Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
10+ years of software development experience delivering and operating large‑scale, distributed systems or platforms, including ownership of multiple services or a significant technical domain.
Experience leading developer relations or technical evangelism efforts at scale in enterprise or platform environments.
Proven expertise in designing and implementing service architectures, including system design (LLD), API design, and data modeling, with strong proficiency in at least one modern programming language and associated ecosystems.
Demonstrated experience driving engineering best practices (testing, observability, performance, reliability, security) and leading complex initiatives from design through production operation.
Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real‑world products, with the ability to safely integrate and operate AI/ML‑enabled components within existing services.
Preferred Qualifications:
Experience with developer productivity, platform engineering, or horizontal core services teams, including ownership of CI/CD tooling and deploying code at scale.
Deep, hands‑on understanding of the
software development lifecycle (SDLC) , CI/CD pipelines, and getting code safely to production in large, distributed systems.
Strong
data science and analytics background ; skilled at combining multiple data sources, applying analytical techniques, and turning findings into actionable insights for engineering leadership.
Hands‑on experience
measuring developer productivity
using frameworks such as DORA or SPACE.
Demonstrated
executive presence
with a track record of translating complex technical and data concepts into clear narratives and data stories for senior engineering and CTO‑level leaders.
Practical experience with
AI developer tools
(e.g., Claude, GitHub Copilot, Cursor, Codex, Kiro), including evaluating adoption, usage depth, and impact on developer workflows and outcomes, with concrete examples of using AI in day‑to‑day work.
Experience building
analytics and reporting that answer executive questions
about AI adoption, productivity impact, and quality/reliability outcomes (e.g., monitoring and interpreting change failure rate and related metrics).
Understanding of causal inference methods to measure the impact of tooling and workflow changes and proficiency in SQL and modern data platform tooling (e.g., Spark, Databricks) for building and maintaining analytical pipelines at scale.
Pay ranges vary by location and may be modified in the future. For example, the cash range in Chicago is $214,500 to $300,000, with potential to increase to $343,000 based on performance. For Seattle, the range is $231,000 to $323,500, with potential to increase to $369,500. For Austin, the range is $231,000 to $323,500, with potential to increase to $369,500. For San Jose, the range is $249,000 to $348,500, with potential to increase to $398,500.
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E‑Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s I‑9 to confirm work authorization.
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