Data Engineer

Fieldwire is a construction technology platform that provides crews with access to plans, tasks, and project updates. The Data Engineer will own the company’s data infrastructure and pipelines, ensuring reliable, scalable, production-ready data for reporting, analytics, and business decision-making. The role will design and maintain data architecture, ETL/ELT workflows, integrations, validation systems, and governance processes.

Responsibilities:

• Design, build, and maintain automated data pipelines that move data from source systems (Salesforce, Xero, Ramp, product databases) into our central data lake and warehouses
• Own the end-to-end data architecture, including storage strategy, processing systems, and pipeline orchestration
• Implement and maintain ETL/ELT workflows that extract, transform, and load data into clean, analytics-ready formats
• Partner with Data Insights Managers and business stakeholders to translate reporting requirements into robust technical data solutions
• Build automated validation and quality-check layers into every pipeline to prevent bad data from reaching reporting layers
• Monitor pipeline health in real time; triage and resolve failures quickly to meet data availability SLAs
• Enforce data standards, naming conventions, schema consistency, and access controls across all systems
• Support integration and maintenance of key tools including Salesforce, Xero, Ramp and Greenhouse into the data lake
• Maintain auditability of all data flows and support compliance and governance requirements
• Collaborate with the DIM TL and Director of Operations on the data roadmap and architectural decisions

Requirements:

• 2-3+ years of experience in a Data Engineering or equivalent role
• Strong proficiency in SQL and at least one scripting language (Python preferred)
• Hands-on experience building and maintaining ETL/ELT pipelines at scale
• Experience with cloud data platforms (e.g. Snowflake, BigQuery, Redshift, Databricks)
• Familiarity with pipeline orchestration tools (e.g. Airflow, dbt, Fivetran, Airbyte)
• Strong understanding of data warehousing concepts, dimensional modelling, and data lake architecture
• Experience integrating SaaS platforms (CRM, ERP, finance systems) via APIs and connectors
• Excellent problem-solving skills with a rigorous approach to data quality and reliability
• Ability to work independently in a fully remote, fast-moving environment
• Strong written communication skills — able to document technical decisions clearly for non-technical stakeholders
• This is a fully remote role based in the United States
• Experience at a SaaS or technology company
• Familiarity with Salesforce data structures and reporting layers
• Exposure to BI tools (Power BI, Looker, Tableau) and understanding of how downstream consumers use data
• Experience with real-time or streaming data pipelines
• Knowledge of data governance frameworks and access control models
• Prior experience supporting a GTM or Finance data stack