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OpenGov is seeking a Data Engineer to join its Data Platform team, supporting the company's AI and ERP solutions for local and state governments across the U.S. The role focuses on building and maintaining scalable data infrastructure that powers analytics, product, and AI initiatives.
Key responsibilities include:
- Stakeholder Engagement: Partner with business stakeholders across Analytics, Operations, GTM, and G&A to translate problem statements into clear data requirements.
- Data Modeling & Transformation: Design and build dimensional and analytical data models in Snowflake using dbt (Cloud/Core). Develop, test, and maintain modular dbt models following best practices including staging, intermediate, and marts layers. Optimize SQL queries and dbt models for performance using Snowflake features like clustering and materialization strategies.
- Pipeline Scheduling & Deployment: Own scheduling and orchestration of dbt jobs with reliability and SLA adherence. Manage CI/CD workflows for dbt and pipeline deployments using GitHub Actions, including automated testing, linting, and environment promotion. Collaborate on AWS resource provisioning via Terraform.
- Data Quality & Analysis: Implement data quality checks and freshness tests within dbt. Perform exploratory data analysis to validate source data, understand distributions, and surface anomalies.
Required qualifications include a Bachelor's degree in Computer Science, Mathematics, Engineering, Statistics, or related field, plus 4–6 years of data engineering or backend engineering experience. Essential skills: hands-on dbt and Snowflake proficiency, CI/CD pipeline experience (GitHub Actions preferred), dimensional modeling expertise, AWS familiarity (S3, Lambda, IAM), advanced SQL, Python proficiency, and strong software engineering practices. Experience with AI-assisted development tools is valued.
Nice-to-have skills include Terraform/IaC experience, workflow orchestrators (Airflow, Dagster, Prefect), dbt Mesh concepts, data ingestion tools (Fivetran, Airbyte, AWS Glue), business application data experience, BI tooling familiarity, and containerized deployments.
