architect and develop scalable data pipelines and models using Snowflake and dbt
design and operate orchestration using Airflow, Dagster, Prefect, or similar
define modeling standards, storage patterns, and performance strategies
collaborate on backend APIs, services, integration layers, and limited frontend interfaces supporting data-driven features
contribute to CI/CD, environment management, and automated pipeline delivery
implement quality checks, lineage, SLAs, and observability
mentor engineers and drive architectural best practices
participate in system design and multi-team architectural planning

Requirements

5+ years of experience in data engineering, data architecture, or platform engineering
Strong experience with dbt (modeling, testing, deployment, environment strategies)
Hands-on experience with orchestration frameworks (Airflow, Dagster, Prefect, or similar)
Deep expertise with data warehousing platforms; e.g. Snowflake, Redshift, etc including performance tuning and RBAC
Strong software engineering fundamentals in Python or Golang; advanced SQL
Deep understanding of distributed systems, event-driven design, microservices, and data platform architecture
Experience with metadata management, lineage tools, and observability technologies (Datadog, Prometheus, OpenTelemetry)
Strong communication skills for leading architectural discussions across technical and non-technical teams

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringdata architectureplatform engineeringdbtAirflowDagsterPrefectPythonGolangSQL

Soft Skills

communicationmentoringcollaborationleadership