About the role
About Higher Logic:
Higher Logic exists to connect people, knowledge, and ideas to improve lives and organizations. Through our community solutions, we empower growth-stage businesses and associations to build a more engaged and meaningful relationship with their customers and members. Higher Logic serves more than 3,000 customers, representing over 350,000 online communities with greater than 200 million users in more than 42 countries worldwide.
Our team is a thriving community of authentic people with diverse experiences and perspectives. We are honest and genuine and believe that sharing ideas and feedback openly helps us to be successful. We believe that diversity and empathy bring us #AllTogether to make us stronger. We learn from failure and successes because both help us to grow and learn. We strive to understand the why behind our actions and bring our best selves to work every day.
JOB SUMMARY
The Associate Data Solutions Engineer supports Higher Logic’s strategic data initiatives by designing, developing, and scaling data pipelines and models that enable analytics, business intelligence, and AI workflows, using both structured and unstructured data. This role is critical in building our data warehouse and enabling AI capabilities across the organization and reports directly to the Chief Data Officer. The engineer works closely with internal stakeholders across departments to ensure data is reliable, accessible, and actionable for both operational and strategic use.
ESSENTIAL DUTIES AND RESPONSIBILITES:
- Build and maintain scalable ETL/ELT pipelines to ingest structured and unstructured data into the data warehouse.
- Develop and optimize data models to support reporting, dashboards, and operational insights.
- Write clean, efficient, and reusable SQL and Python code to transform raw data into business-ready outputs.
- Collaborate with analytics and business stakeholders to understand data requirements and deliver practical solutions.
- Monitor pipeline performance and ensure reliability, accuracy, and timeliness of data flows.
- Design frameworks for triggering AI workflows based on business rules and data events.
- Serve as a subject matter expert on data best practices, including schema design, data governance, and data security.