Sr. Data Engineer

We're looking for an experienced Data Engineer who can design and run the pipelines that turn messy, multi-source, first-party data into clean, reliable, analysis- and model-ready datasets. Complex transformation is the core of this role; you'll be the person who makes sure the data powering our analytics, personalization, and AI is trustworthy and fast.

Responsibilities:

• Build and maintain batch and streaming pipelines that ingest customer and behavioral data across many sources and channels (web, app, email, SMS, WhatsApp, CRM, ad platforms).
• Design and own complex transformations for cleaning, normalizing, deduplicating, joining, and modeling data across sources so it stays consistent and dependable.
• Build and maintain the data models and warehouse/lakehouse layers that power analytics, personalization, and ML.
• Own data quality, lineage, and observability: tests, monitoring, alerting, and clear documentation.
• Optimize pipelines for performance and cost across the cloud stack.
• Partner with product, analytics, and AI/ML teams so the data they need is available, well-shaped, and reliable.

Requirements:

• 6+ years in data engineering, with a clear track record of complex data transformation at scale.
• Strong SQL and Python. Solid experience with ETL/ELT design, data modeling, and orchestration (e. g., Airflow, dbt).
• Experience with a modern data warehouse or lakehouse (e. g., Redshift, BigQuery, Snowflake).
• Cloud experience: AWS and GCP are preferred. Comfort with data-quality frameworks, version control (Git), and CI/CD.

Nice to Have:

• Product exposure experience working on a data product or closely alongside product teams (a strong plus).
• Streaming / real-time data experience (Kafka, Kinesis) given our real-time personalization needs.
• Marketing, eCommerce, or customer/behavioral data experience.
• Familiarity with our stack: FastAPI, Python, SQL, AWS, GitHub, Jenkins.