Analytics Engineering Co-Op

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and construct Databricks data models that consolidate fragmented logic into a single source of truth for reporting and analysis at the Student Success Center.

• Standardize components of the semantic layer and metric definitions across various reports, dashboards, and leadership presentations.

• Enhance data quality in the transformation layer through validation, freshness assessments, and reconciliation procedures.

• Collaborate with Business Technology concerning upstream data sources, pipeline modifications, and governance processes.

• Convert business requirements into technically robust solutions and effectively convey technical possibilities to operators.

• Transform a recurring manual report into a self-sustaining modeled Power BI data product while quantifying time savings.

• Document data lineage, definitions, rationale, and existing deliverables comprehensively.

• Work alongside Student Success Center stakeholders to facilitate improved workflows and programmatic analytics solutions.

• Contribute to the development of standardized semantic layer components and operational metrics.

• Assess adoption rates, hours saved, and enhancements within the Databricks environment.

⛳️ Requirements

• Proficient in SQL, including the use of joins, aggregations, query debugging, and resolving data issues within queries, notebooks, and jobs.

• Practical experience with Python; capable of navigating existing scripts and workflows and implementing solutions with AI assistance.

• Understanding of foundational database management concepts such as keys, grains, and normalization.

• Strong analytical judgment demonstrated in a real-world business context.

• Proven ability to navigate ambiguity and drive measurable outcomes for stakeholders.

• Excellent verbal and written communication skills, effectively engaging both technical and non-technical stakeholders.

• Previous experience in a data engineering and/or analytics environment working collaboratively with others.

• Knowledge and experience with Databricks, Snowflake, or other cloud data platforms.

• Comfort with technical documentation and project management within an engineering framework.

• Familiarity with data transformation tools and confidence in utilizing AI tools within an analytics workflow.

• Availability for full-time work, 40 hours per week, Monday through Friday.

• Capability to engage in a co-op from January 2027 to June 2027, with flexibility for academic commitments.

🏝️ Benefits

• Full-time co-op experience, 40 hours per week, Monday through Friday.

• Opportunity for practical, real-world exposure.

• Chance to significantly impact strategy and business outcomes.

• Freedom to suggest and test better methodologies.

• Equal opportunity employer that promotes a diverse and inclusive workforce.