Support 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.
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.
Partner with cross-functional teams to align data assets with enterprise goals, AI enablement, and automation strategies.
Drive adoption of new data tools and methodologies, such as DBT, Iceberg, or similar modern data stack technologies.
Report directly to the Chief Data Officer and work closely with internal stakeholders across departments to ensure data is reliable, accessible, and actionable.
Requirements
Proficiency in SQL and Python for data processing and transformation.
Familiarity with modern data warehousing tools (e.g., DBT, Iceberg, Databricks, or similar).
Experience working with both structured and unstructured data sources.
Understanding of data quality, observability, and monitoring principles.
Strong communication and collaboration skills to support cross-functional work.
Ability to work independently and adapt to evolving data needs.