Way is seeking an experienced Senior Data Engineer to establish and lead their data infrastructure as an early member of their data team. This role will be responsible for building their 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 their organization.
Requirements
- 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)
Responsibilities
- 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)
- Develop and maintain Python-based data processing frameworks and utilities
Other
- 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
- 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
