Data Engineer
Role details
Job location
Tech stack
Job description
We're seeking an experienced Senior Data Engineer to help shape the future of hearing care through cutting edge data infrastructure. You'll take full ownership of the complete data lifecycle from ingestion and transformation to powering AI agents and LLMs through our semantic layer. This isn't traditional analytics; you're building data products that drive intelligent automation and decision making at scale., * Design and build robust, high performance data pipelines using our modern stack (Airflow, Snowflake, Pulsar, Kubernetes) that feed directly into our semantic layer and data catalog
- Create data products optimized for consumption by AI agents and LLMs where data quality, context, and semantic richness are crucial
- Structure and transform data to be inherently machine readable, with rich metadata and clear lineage that powers intelligent applications
- Take responsibility from raw data ingestion through to semantic modeling, ensuring data is not just accurate but contextually rich and agent ready
- Champion best practices in building LLM consumable data products, optimize for both human and machine consumers, and help evolve our dbt transformation layer
- Built data products for AI/LLM consumption, not just analytics dashboards
Requirements
- 5+ years of hands on experience with complex ETL processes, data modeling, and large scale data systems
- Production experience with modern cloud data warehouses (Snowflake, BigQuery, Redshift) on AWS, GCP, or Azure
- Proficiency in building and optimizing data transformations and pipelines in python
- Experience with columnar storage, MPP databases, and distributed data processing architectures
- Ability to translate complex technical concepts for diverse audiences, from engineers to business stakeholders
- Experience with semantic layers, data catalogs, or metadata management systems
- Familiarity with modern analytical databases like Snowflake, BigQuery, ClickHouse, DuckDB, or similar systems
- Experience with streaming technologies like Kafka, Pulsar, Redpanda, or Kinesis