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.
All other duties as assigned.

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.

Competitive compensation.
Comprehensive health benefits package.
401(k) plan with employer match.
Healthcare and dependent-care flexible spending account.
Company short-term and long-term disability insurance.
Company culture that recognizes its employees.
Room for growth and development and management that cares about your professional growth and will help you achieve your goals.
Significant advancement opportunities for outstanding performers.

Associate Data Solutions Engineer

Key skills