Data Engineer

About the role

OpenGov is looking for a skilled and solution-oriented Data Engineer to join our growing Data team. In this role, you will be the bridge between business stakeholders and data solutions—translating complex analytical and AI use case requirements into reliable, scalable data products. You will work hands-on with Snowflake, dbt, and Airflow to model, transform, and orchestrate data that powers decision-making across the organization. You think in terms of data models, business domains, and consumption patterns. You partner closely with analytics, product, and engineering teams to understand their needs and deliver data solutions that are well-structured, well-documented, and production-ready.

What You’ll Own

• Stakeholder Engagement & Requirement Gathering: Partner with business stakeholders across Analytics, Operations, GTM, and G&A to understand problem statements and translate them into clear data requirements.
• Data Modeling & Transformation: Design and build dimensional and analytical data models in Snowflake using dbt (Cloud/Core) that serve as the single source of truth for business domains. Develop, test, and maintain dbt models following best practices—including modular layering (staging, intermediate, marts), documentation, and data tests. Optimize SQL queries and dbt models for performance, leveraging Snowflake features such as clustering, materialization strategies, and query profiling.
• Data pipeline Orchestration: Build and manage Airflow DAGs to orchestrate multi-step data pipelines, ensuring reliability, observability, and SLA adherence. Own end-to-end delivery of data products—from raw source data ingestion through transformation to governed, consumption-ready datasets. Collaborate with the Data Platform team on pipeline integration, CI/CD workflows, and adherence to shared coding and deployment standards.
• Data Quality & Analysis: Implement data quality checks and freshness tests within dbt to proactively catch issues before they reach consumers. Perform exploratory data analysis to validate source data, understand distributions, and surface data anomalies during scoping and build phases. Work with stakeholders to define and monitor data SLAs, ensuring data products are trustworthy and consistently delivered.

What You Bring

• 4–6 years of experience in data engineering, analytics engineering, or a similar related role.
• Snowflake & DBT Proficiency: Hands-on experience building and maintaining dbt projects in Snowflake—you understand model layering, ref() dependencies, materialization strategies, and how to write performant SQL.
• Airflow Expertise: Proven ability to author and manage production Airflow DAGs for orchestrating complex, multi-step data workflows.
• Data Modeling Skills: Solid understanding of dimensional modeling concepts (star schema, slowly changing dimensions) and the ability to design models that balance clarity, performance, and flexibility.
• SQL Mastery: Advanced SQL skills with the ability to write complex transformations, window functions, and optimization techniques in Snowflake.
• Python: Proficiency in Python for data manipulation, pipeline scripting, and automation.
• Business Acumen: You can sit in a discovery session with a business stakeholder, understand their analytical problem, and translate it into a well-structured data model.
• Data Analysis: Comfort exploring raw data, identifying quality issues, and communicating findings clearly to stakeholders.
• Software Engineering Practices: You treat data code like software—version-controlled, peer-reviewed, tested, and documented.
• Strong communication and collaboration skills, with the ability to work across technical and non-technical audiences.
• Bachelor's degree in Computer Science, Engineering, Statistics, or a related field.