Data Engineer, Notifications

Responsibilities

• Own data architecture end-to-end: define capture, modeling, and serving of critical business data; implement in production with decisions on storage, compute, and SLAs.
• Build mission-critical pipelines: develop and operate batch workflows for high-volume notification events with guarantees on latency, completeness, and accuracy.
• Design and implement canonical models: create domain-oriented data models as source of truth for analytics, ML, and applications; enforce standards, ownership, and contracts.
• Enforce data quality at scale: build tests, lineage, monitoring, and reconciliation systems.
• Automate operational workflows: partner to eliminate manual handoffs and reconcile data across services and warehouses.
• Enable insights and experimentation: support analytics, ML, and product teams with high-quality data assets.

Requirements

• 5+ years experience in data or software engineering.
• Strong experience building production-grade data pipelines with SLAs, monitoring, alerting.
• Deep expertise in SQL (complex models, dependencies, optimization).
• Production-grade code in Python or SQL, CI/CD, infrastructure-as-code.
• Hands-on with ingestion (Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), observability (Monte Carlo, Great Expectations).
• Operated cloud data warehouses (Snowflake, BigQuery, Redshift): schema design, cost optimization, tuning.
• Proven with large-scale datasets (hundreds of millions rows/day).
• Data models balancing analytics, ML, operational use cases.
• Strong systems thinking (correctness, latency, cost, maintainability).
• Self-starter, autonomous, exceptional communication.