Data Engineer

In the short term, this role partners with stakeholders to clarify questions and requirements, acquires/cleans/validates data (e.g., Flow metrics and Atlassian/Jira data), delivers recurring and ad?hoc analysis, and produces executive?ready dashboards, visualizations, and narratives. In the long term, it evolves into end?to?end data engineer, designing data models and scalable pipelines, automating ingestion/validation/monitoring, building integrations and reusable curated datasets, and supporting AI/ML accuracy and reliability practices, so the team has trusted high quality data powering our custom applications., * In the short term, this role partners with stakeholders to clarify questions and requirements, acquires/cleans/validates data (e.g., Flow metrics and Atlassian/Jira data), delivers recurring and ad?hoc analysis, and produces executive?ready dashboards, visualizations, and narratives. In the long term, it evolves into end?to?end data engineer, designing data models and scalable pipelines, automating ingestion/validation/monitoring, building integrations and reusable curated datasets, and supporting AI/ML accuracy and reliability practices, so the team has trusted high quality data powering our custom applications.

5+ years in analytics/BI who is robust in SQL, and excel, and comfortable working with large datasets end?to?end (acquire, clean, validate, and analyze).

They should have hands-on experience building executive-ready dashboards (Tableau/Power BI) and communicating insights clearly to non-technical stakeholders, plus solid data wrangling/automation skills in Python (TypeScript acceptable).

For the growth path into data engineering, prefer exposure to ETL concepts, basic data modeling (star schema/fact-dimension/knowledge base), Git/version control, and familiarity with cloud/data platforms and orchestration (e.g., AWS services) along with a track record of learning quickly and productionizing repeatable reporting.