5+ years of hands-on data engineering experience with increasing responsibility
Preferred 7+ years in data engineering roles
Proven track record of building data systems from scratch
Experience working as a solo data engineer or on small teams
Strong experience with cloud platforms and their data services
Responsibilities
Design and implement a comprehensive data lake architecture
Build scalable ETL/ELT pipelines for data processing
Establish data ingestion frameworks from various sources
Architect automated data quality monitoring systems
Create robust data warehousing solutions for analytics
Collaborate with product teams to identify analytical requirements
Benefits
Highly competitive salary and generous equity
100% paid medical, dental, and vision coverage
401K benefits and travel-related perks
$500 Annual Experience Stipend for client partner activities
Full Job Description
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
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.
