Staff Data Architect

This role is eligible for our hybrid work model: Two days in-office
 

Our Technology team is the backbone of our company: constantly creating, testing, learning and iterating to better meet the needs of our customers. If you thrive in a fast-paced, ideas-led environment, you’re in the right place.
 

Why this job’s a big deal:

As a Staff Data Architect for Customer Growth, you will be the technical beacon and architectural anchor for the data ecosystems that drive our customer acquisition, retention, and engagement strategies. This is a high-impact, leadership-by-influence role where you will not just write code, but design the future-proof frameworks that empower multiple engineering squads.
 

You will evaluate complex technical trade-offs, champion engineering excellence, and foster a culture of innovation. Operating across the entire Customer Growth portfolio, you will collaborate closely with product management, data science, and business leaders to turn massive datasets into strategic growth levers.
 

In this role, you will get to:
 

• Architecture & Framework Design: Design, build, and evolve robust, scalable, and highly reliable data architectures and framework-level designs that support real-time personalization, marketing automation, and advanced customer analytics.

• Technical Decision Making & Trade-off Analysis: Act as the ultimate sounding board for complex data challenges. Evaluate competing technologies and methodologies (e.g., batch vs. streaming, self-hosted vs. managed services, various data lakehouse architectures) and present objective, clear trade-off analyses to stakeholders.

• Best Practices & Governance: Define, document, and evangelize global engineering best practices, data governance frameworks, security standards, and CI/CD automation patterns across the portfolio.

• Cross-Portfolio Collaboration: Break down silos. Work seamlessly with cross-functional teams within the Customer Growth domain to ensure data infrastructure aligns perfectly with product roadmaps and business goals.

• Innovation & R&D: Stay ahead of the curve. Continually research, prototype, and introduce emerging technologies and innovative paradigms (such as Data Mesh, advanced identity resolution, or real-time feature stores) to keep our growth engine competitive.

• Mentorship & Technical Guidance: Act as a force multiplier. Guide, unblock, and elevate senior and mid-level engineers by conducting rigorous code/architecture reviews and hosting knowledge-sharing sessions.
   

Who you are:

• Bachelor’s degree or higher in Computer Science or related field.

• 8+ years of experience designing and implementing distributed data processing systems utilizing tools like Apache Spark, Flink, Kafka, or Delta Lake/Iceberg.

• Deep expertise in major cloud platforms (AWS, GCP, or Azure) and cloud-native data warehousing solutions like Snowflake, BigQuery, or Databricks.

• Proven track record of building reusable data libraries, custom tooling, or internal platforms that accelerated development for other engineering teams.

• Expert-level knowledge of data modeling paradigms (Data Vault, Kimball, Star Schema) tailored for complex customer journeys and behavioral data.

• Highly proficient in Python, Scala, or Java, alongside expert-level SQL.

• A natural curiosity to challenge the status quo and a history of successfully introducing innovative data solutions to business problems.

• Exceptional communication skills with the ability to articulate complex technical concepts to non-technical business partners, and a proven ability to lead through influence rather than authority.

• Ability to look at multiple viable technical paths, weigh the immediate business needs against long-term technical debt, and confidently steer the team toward the optimal choice.

• Illustrated history of living the values necessary to Priceline: Customer, Innovation, Team, Accountability and Trust

• The Right Results, the Right Way is not just a motto at Priceline; it’s a way of life. Unquestionable integrity and ethics is essential
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