Build and lead Way’s data infrastructure from the ground up. Design cloud-native data lakes, scalable batch and real-time ETL/ELT pipelines, ingestion frameworks, data warehouses, orchestration, streaming systems, data quality monitoring, and DataOps practices. Develop Python and SQL-based data solutions, infrastructure as code, feature stores, dashboards, and self-service analytics. Partner with product and business teams on metrics, predictive modeling, and experimentation while establishing data-driven practices.
ABOUT WAY
Way is building the AI, data, and infrastructure layer for the experience economy.
As artificial intelligence automates labor and people reclaim time, the shift toward spending on experiences over things only accelerates. Way sits at the center of that shift as the platform, intelligence layer, and curated marketplace on which experiences are created, distributed, and sold.
Founded in 2020 and headquartered in Austin with offices in Paris and San Francisco, Way built the category of experiences in hospitality from the ground up, during a pandemic that had shut the industry down. Leading global travel, retail, lifestyle, and hospitality brands leverage Way, including Hyatt, Hilton, Alaska Airlines, Aspen, Piaget, and countless others.
Way’s position is layered by design: a proprietary data network built on millions of experiential data points, the system of record for experiential operations, an e-commerce layer embedded directly into partners’ customer journeys, and a marketplace through Partner Exchange, where brands across hospitality, travel, lifestyle, and retail co-create and co-sell experiences with one another. Every brand that joins makes the network more valuable to every brand already on it.
That combination of data, workflow, distribution, and network effects is not something that can be vibe-coded into existence. It compounds. It is what positions Way as the durable infrastructure for the experience economy regardless of how the technology landscape evolves.
Way is backed with $22m in capital from Tiger Global and strategic family offices and angel investors. The company has mid-8 figures of ARR from a global enterprise customer set, with outstanding growth and efficiency metrics.
As artificial intelligence automates labor and people reclaim time, the shift toward spending on experiences over things only accelerates. Way sits at the center of that shift as the platform, intelligence layer, and curated marketplace on which experiences are created, distributed, and sold.
Founded in 2020 and headquartered in Austin with offices in Paris and San Francisco, Way built the category of experiences in hospitality from the ground up, during a pandemic that had shut the industry down. Leading global travel, retail, lifestyle, and hospitality brands leverage Way, including Hyatt, Hilton, Alaska Airlines, Aspen, Piaget, and countless others.
Way’s position is layered by design: a proprietary data network built on millions of experiential data points, the system of record for experiential operations, an e-commerce layer embedded directly into partners’ customer journeys, and a marketplace through Partner Exchange, where brands across hospitality, travel, lifestyle, and retail co-create and co-sell experiences with one another. Every brand that joins makes the network more valuable to every brand already on it.
That combination of data, workflow, distribution, and network effects is not something that can be vibe-coded into existence. It compounds. It is what positions Way as the durable infrastructure for the experience economy regardless of how the technology landscape evolves.
Way is backed with $22m in capital from Tiger Global and strategic family offices and angel investors. The company has mid-8 figures of ARR from a global enterprise customer set, with outstanding growth and efficiency metrics.
We are seeking an experienced Senior Data Engineer to establish and lead our data infrastructure as an early member of our data team. This role will be responsible for building our entire data platform from the ground up, implementing a comprehensive data lake and pipeline architecture, and establishing a culture of data-driven decision-making throughout our organization. The ideal candidate will serve as both a technical leader and data advocate, driving automation excellence while flexing into data science and analytics responsibilities as needed.
Key Responsibilities
Data Infrastructure & Pipeline Architecture
- Design and implement a comprehensive data lake architecture using modern cloud-native technologies
- Build scalable ETL/ELT pipelines for real-time and batch data processing across all data sources
- Establish data ingestion frameworks to collect data from application APIs, third-party services, and databases
- Architect automated data quality monitoring, validation, and alerting systems
- Create robust data warehousing solutions optimized for analytics and business intelligence
- Implement DataOps practices with automated testing and deployment pipelines (CI/CD for data)
Data Engineering & Analysis
- Develop and maintain Python-based data processing frameworks and utilities
- Build an automated data pipeline orchestration using Apache Airflow or similar tools
- Create streaming data processing solutions using Apache Kafka, Kinesis, or Pub/Sub
- Implement infrastructure as code for all data platform components (Terraform, CloudFormation)
- Establish feature stores and data models that support both operational and analytical workloads
- Optimize data storage costs and query performance across the entire platform
- Collaborate with product and business teams to identify key metrics, KPIs, and analytical requirements
- Build automated reporting dashboards and self-service business intelligence tools
- Support predictive modeling initiatives and A/B testing frameworks
Required Experience
- Minimum 5+ years of hands-on data engineering experience with increasing responsibility
- Preferred 7+ years in data engineering, analytics engineering, or data platform roles
- Proven track record of building data systems from scratch or leading data infrastructure transformations
- Experience working as a solo data engineer or in small, autonomous data teams
Required Technical Skills
- Python proficiency required - demonstrated experience building data pipelines, ETL frameworks, and automation scripts
- SQL expertise - advanced knowledge of complex queries, performance optimization, and data modeling
- Strong experience with cloud platforms (AWS, GCP, or Azure) and their data services
- Proficiency with data lake technologies (Delta Lake, Apache Iceberg, or Apache Hudi)
- Experience with data orchestration tools (Apache Airflow, Prefect, Dagster, or similar)
- Knowledge of streaming data technologies (Apache Kafka, Kinesis, Pub/Sub)
- Familiarity with data warehouse technologies (Snowflake, BigQuery, Redshift, Databricks)
- Understanding of containerization (Docker, Kubernetes) and infrastructure as code
- Experience with version control systems (Git) and collaborative development workflows
Preferred Qualifications
- Background in real-time analytics and event-driven architectures
- Previous experience in startup or fast-paced environments
- Understanding of data privacy regulations (GDPR, CCPA) and security best practices
- Experience with performance monitoring and observability tools
- Knowledge of dimensional modeling and data warehouse design patterns
Why Join Way?
- Compensation: competitive salary calibrated to experience, and meaningful equity in a sustainably growing company with real value creation already realized.
- Coverage: full health, dental, and vision.
- The work: direct access to the world’s most recognized consumer brands and the mandate to move quickly on their behalf.
- The tools: the best available, and the expectation that you use them to raise your own ceiling.
- Experience firsthand: an annual hotel and travel stipend at the properties and partners in Way’s global ecosystem.
- Where you’ll be: in a beautiful office in Austin, San Francisco, or Paris.
Way is a company for people who want to do the best work of their careers at a technology company and in an industry that will continue to flourish as humanity embraces AI. The standard for building an exceptional software company has changed, and Way is being built to meet it, with urgency, ownership, and a pace of execution well above the industry norm. The market direction is not in question. As AI absorbs more and more work, humans have more time and more money to spend on experiences, and the brands they spend it with need infrastructure they cannot build themselves.
Way Austin, Texas, USA Office
CBD Austin
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