Senior Data Engineer

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

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 know that 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 (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

What you’ll do:

Data Engineering & Architecture:

• Design and implement a scalable data platform to power marketing automation, personalization, and MarTech initiatives.
• Architect and manage robust data pipelines and ETL processes to ensure accuracy, performance, and reliability.
• Uphold data governance, security best practices, and regulatory complianceacross all marketing data workflows.
• Lead development across the full data lifecycle, including capture, processing,storage, and distribution.
• Leverage AWS best practices and services (e.g., compute, storage, and databases) to build efficient, cloud-native solutions.

Integration & Data Flow Optimization

• Act as a role-model with impact-focus, innovation, continuous improvement and excellence within the team.
• Implement, create change management for and maintain best practices best practices for data ingestion, creation, enrichment and management, including data modeling, ETL processes, data warehousing, real-time data streaming, processing, storage, efficiency and real time insights.
• Create and execute plans for cost-effective, efficient, resilient, scalable and operational data infrastructure.
• Lead the evolution of ML platform to help accelerate business impact bootstrapping AI.
• Lead efforts to integrate data across multiple marketing and sales platforms, including CRM, email, automation platforms, and analytics tools, such as Salesforce, Adobe Marketing Cloud, and Marketo.
• Collaborate with MarTech, analytics, and IT teams to enhance the data flow between marketing platforms, ensuring seamless data access and integration for campaigns and reporting.
   

Innovation & Continuous Improvement

• Stay current with data engineering trends, MarTech advancements, and emerging technologies that can enhance the effectiveness and efficiency of marketing operations.
• Drive continuous improvement initiatives to refine data engineering processes and leverage new tools or frameworks that support automation and scalability.
• Lead or participate in data-related pilot projects, testing new solutions and capabilities that could enhance marketing automation and analytics.
• Develop scalable and highly-performant distributed systems with everything this entails (availability, monitoring, resiliency).

Who you are:

• Bachelor’s degree; or equivalent related professional experience.
• 10+ years of development experience, particularly in using marketing acquisition technologies to deliver automation of multiple channels and drive operational efficiencies. This is a Staff Data Engineer/Technical Lead equivalent role.
• Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
• Strong knowledge of Python, SQL, Airflow, ETL, and expertise with data processing technologies and query authoring (SQL).
• Proven ability to design and optimize batch and real-time data pipelines and systems, ensuring their quality, performance, and stability.
• Proven track record of designing and managing large-scale data infrastructures in a complex, fast-paced environment with preferable similar experience scaling data in a fast growing late-stage startup.
• Expertise in cloud platforms and big data technologies including proficiency in database management systems, ML and AI systems, data warehousing solutions.
• Experience with data integration tools and techniques, processes and real-time datastreaming and processing.
• Experience operationalizing ML/AI models using AWS SageMaker, Bedrock, Databricks MLOps frameworks or others in production environments