Own data architecture end-to-end. Define how we capture, model, and serve critical business data—then implement it in production.
Build mission-critical pipelines. Develop and operate batch data workflows that process high-volume events related to notifications with tight guarantees for latency, completeness, and accuracy.
Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and production applications.
Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, self-healing, maintainable data assets.
Requirements
5+ years of experience in the data or software engineering domain
Strong experience building and maintaining production-grade data pipelines with clear SLAs, monitoring, and alerting
Deep expertise in SQL, including complex model graphs, dependency management, and performance optimization
Comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows
Deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations)
Operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning
Proven track record working with large-scale datasets (hundreds of millions of rows per day)
Experience designing data models that balance analytics, ML, and operational debugging use cases
Strong systems thinking — consider correctness, latency, cost, and maintainability together
Self-starter ethic, thriving under a high level of autonomy
Exceptional interpersonal and communication skills in cross-functional environments
Tech Stack
Airflow
Amazon Redshift
BigQuery
Cloud
Kafka
Python
Spark
SQL
Benefits
Generous Holiday and Time off Policy
Health Insurance options including Medical, Dental, Vision
Work From Home Support
Home office setup allowance
Monthly allowance for cell phone and internet
Care benefits
Monthly allowance for wellness
Annual allowance towards Childcare
Lifetime benefit for family planning, such as adoption or fertility expenses
Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
Monthly allowance to dogfood the app
Paid parental leave + one month gradual return to work