Platform Architecture & Automation
•Design and evolve the architecture for a scalable analytics engineering platform, centered on dbt Cloud and GitHub-driven CI/CD.
•Establish deployment patterns and environment strategies (dev/test/prod) for dbt projects, including dependency management and release controls.
•Build automation around platform operations (quality gates, approvals, notifications, versioning, documentation generation).
Data CI/CD with GitHub & GitHub Actions
•Implement and maintain GitHub Actions workflows for data pipeline preparation and deployment, including: - Pull request validation (dbt compile, dbt build/test, linting, docs checks)
•Merge-to-main deployment orchestration (dbt Cloud job triggers, environment promotion)
•Scheduled workflows (nightly validation runs, drift detection, metadata checks)
•Create reusable workflow templates and “golden path” pipelines for dbt repositories.
•Integrate CI/CD with code quality and security tooling (secret scanning, dependency alerts, branch protection alignment).dbt Cloud Architecture & Enablement
•Own/guide dbt Cloud project setup, job design, scheduling strategy, and environment configuration.
•Define conventions for dbt Cloud job separation (CI jobs vs deployment jobs), including job triggers from GitHub events.
•Improve performance and reliability of dbt runs (state-aware builds, selective execution patterns, artifact usage).
•Support authentication/authorization patterns across dbt Cloud, GitHub, and data warehouse. Standards, Governance & Best Practices
•Establish and enforce GitHub best practices for data development: - branching strategy, PR templates, CODEOWNERS, semantic versioning/tagging
•standardized repository structure for dbt projects and shared packages
•Define release processes for data transformations (promotion, approvals, rollback approach).
•Improve developer experience through documentation, onboarding guides, and internal enablement.
Collaboration & Continuous Improvement
•Partner with data stakeholders to identify pain points and deliver architectural improvements.
•Provide technical leadership on CI/CD patterns for analytics engineering and platform modernization.
•Monitor pipeline health and drive ongoing improvement
Required
•4+ years in data engineering, analytics engineering, or platform engineering with strong CI/CD ownership.
•Strong hands-on experience with GitHub (PR workflows, branch protections, repo governance).
•Strong hands-on experience building GitHub Actions workflows (YAML, reusable workflows, secrets, environments).
•Strong experience with dbt Cloud (projects, jobs, environments, CI features, artifacts).
•Proven experience designing deployment workflows and automation for data platforms.
•Strong SQL and solid understanding of data warehouse patterns (e.g., Snowflake/BigQuery/Redshift/Databricks SQL).
