Data Engineer III

Posted 9 Hours Ago
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Bangalore, Bengaluru Urban, Karnataka, IND
Hybrid
Senior level
AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Helping travelers explore the world. One journey at a time.
The Role
Design, build, and operate scalable batch and streaming data pipelines, analytics layers, and impression data models to support ad inventory forecasting. Ensure data quality, observability, and performance; collaborate with engineers, data scientists, and product teams to translate requirements into reliable, production-grade data solutions and integrate AI/ML capabilities where appropriate.
Summary Generated by Built In

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.


Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

Introduction to the team

We build the intelligence layer for Expedia Group’s advertising supply. Our systems forecast ad inventory, track delivery accuracy, and flag at‑risk campaigns across global markets. Advertisers use our forecasts to plan and book with confidence; Revenue Operations uses our risk signals to prevent under-delivery.

As a Data Engineer III on M&I Forecasting, you will own and scale the data foundations behind ad inventory forecasting. You’ll design, build, and operate pipelines, analytics layers, and impression data models that power forecast accuracy measurement, pacing analysis, and delivery risk detection across global markets. You’ll drive data quality, lineage, and observability, partnering with data science and engineering to improve forecast performance.

In this role, you will:
· Design, build, and enhance scalable, secure, and reliable data pipelines and services that enable analytics, experimentation, and product features across multiple business domains.
· Develop, optimize, and maintain batch and streaming data processing solutions, including data modeling, schema evolution, and API design to support downstream consumers and applications.
· Implement robust data quality, validation, monitoring, and observability practices to ensure accuracy, completeness, and timely availability of data for stakeholders.
· Collaborate with engineers, product managers, analysts, and data scientists to translate business and analytical requirements into well-architected data solutions and reusable components.
· Apply and extend engineering best practices for performance, reliability, and cost efficiency, including testing, CI/CD, deployment automation, and operational runbooks for data systems.
· Safely integrate and operate AI/ML‑enabled solutions that improve outcomes, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.

Minimum Qualifications:
· Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
· 5+ years of relevant professional experience
· Proficiency in at least one modern programming language used for data engineering (such as Java, Scala, Python, or similar), along with strong skills in SQL and data modeling for analytical and operational use cases.
· Hands-on experience with data processing frameworks and storage technologies (for example, distributed processing, stream processing, and large-scale data warehouses or data lakes), with clear ownership for the reliability and performance of services you build.
· Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including integrating AI/ML‑enabled capabilities into data pipelines under established guidelines.

Preferred Qualifications:
· Demonstrated experience designing and evolving end-to-end data architectures for complex domains, including system design (LLD), API design, and schema/data model definition to support high-scale, multi-tenant use cases.
· Proven track record operating large-scale data systems in production, including performance tuning, capacity planning, monitoring/alerting, incident response, and continuous improvement of reliability and cost efficiency.
· Experience driving technical direction for data solutions within a team or domain, influencing data standards, tooling, and best practices, and mentoring other engineers on data engineering patterns.
· Strong background using experimentation, metrics, and data-driven insights to guide technical decisions, optimize pipelines, and improve the usability and discoverability of data across multiple products or domains.
· Safely integrates and operates AI/ML‑enabled solutions that improve outcomes, with hands-on experience enabling AI-powered analytics, features, or developer workflows on data platforms (for example, feature pipelines for ML models, AI-assisted data quality, or intelligent observability), and familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products.

Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.


About Expedia Group

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.


Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.


Equal Opportunity

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, religion, gender, sexual orientation, national origin, disability or age.

Skills Required

  • Bachelor's degree in Computer Science or related technical field, or equivalent professional experience.
  • 5+ years of relevant professional experience.
  • Proficiency in at least one modern data engineering language (Java, Scala, Python) and strong SQL skills.
  • Experience with data modeling for analytical and operational use cases.
  • Hands-on experience with data processing frameworks and storage technologies (distributed processing, stream processing, large-scale data warehouses or data lakes).
  • Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to products and pipelines.
  • Designing and evolving end-to-end data architectures, API design, and schema/data model definition for high-scale use cases.
  • Operating large-scale data systems in production: performance tuning, capacity planning, monitoring/alerting, incident response.
  • Driving technical direction, influencing data standards and tooling, and mentoring other engineers.
  • Using experimentation, metrics, and data-driven insights to guide technical decisions and improve pipeline usability.
  • Hands-on experience enabling AI-powered analytics, feature pipelines, or intelligent observability on data platforms.

What the Team is Saying

Christos Rigas

Expedia Group Compensation & Benefits Highlights

  • Wellbeing & Lifestyle Benefits Travel and wellness stipends, employee travel discounts, and access to industry credentials create distinctive lifestyle value aligned with the company’s mission. Feedback suggests these perks are widely valued and complemented by programs like charitable matching and volunteer time.
  • Parental & Family Support Paid parental leave for all parents, additional time for birthing parents, caregiving leave, and fertility/family‑building support indicate comprehensive family backing. Immediate eligibility and flexible return‑to‑work options further strengthen this area.
  • Healthcare Strength Employer‑provided medical options are positioned as locally competitive and are supplemented by mental‑health platforms and neurodiversity coaching. Health coverage is regarded positively, with multiple support pathways beyond standard insurance.

Expedia Group Insights

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The Company
HQ: Seattle, WA
16,000 Employees
Year Founded: 1996

What We Do

Expedia Group, Inc. is the global travel marketplace with one purpose: to help travelers explore the world, one journey at a time. Expedia Group™ connects travelers, partners, and advertisers through its trusted brands, leading technology, and rich first-party data, delivering predictive, personalized experiences that shape the future of travel. Expedia Group’s ecosystem includes three flagship consumer brands – Expedia®, Hotels.com®, and Vrbo® – the largest B2B travel business, and a premier advertising network. Guided by an experienced and passionate global team, Expedia Group helps millions of travelers in more than 70 countries explore the world with confidence and ease.

Why Work With Us

Life at Expedia Group starts with the people and is shaped by how we work together. You’ll join a global community of curious teammates from different backgrounds, locations, and disciplines. Day to day, that means sharing ideas, taking ownership, and solving problems together.

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Expedia Group Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
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