Analytics Engineering Co-Op

Risepoint

. Design and build Databricks data models consolidating scattered logic into a source of truth for Student Success Center reporting and analysis .

Posted 9/29/2026full-timeRemote • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Databricks data modeling, SQL, and Python to create efficient data solutions and improve data quality. Strong communication skills facilitate collaboration with stakeholders to drive analytics and reporting improvements.

Highest-signal resume keywords

Databricks Data ModelingSQL Query DebuggingPython ScriptingData Transformation ToolsTechnical Documentation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData ModelingData Quality ValidationData Lineage DocumentationDatabase Management ConceptsAnalytical JudgmentData EngineeringCloud Data PlatformsAI Tooling

Soft Skills

Strong Verbal CommunicationStrong Written CommunicationAnalytical Problem SolvingCollaboration

Tools & Technologies

DatabricksSnowflakePower BIData Transformation Tools

Industry Keywords

Data AnalyticsBusiness TechnologyStakeholder EngagementGovernanceOperational Metrics

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Design and build Databricks data models consolidating scattered logic into a source of truth for Student Success Center reporting and analysis
Standardize semantic layer components and metric definitions across reports, dashboards, and leadership decks
Improve transformation-layer data quality through validation, freshness, and reconciliation checks
Partner with Business Technology on upstream data sources, pipeline changes, and governance
Translate business needs into technically sound solutions and communicate technical possibilities to operators
Turn a recurring manual report into a self-maintaining modeled Power BI data product and quantify time savings
Document data lineage, definitions, reasoning, and existing deliverables
Coordinate with Student Success Center stakeholders to enable better workflows and programmatic analytics solutions
Contribute to standardized semantic layer components and operational metrics
Measure adoption, hours returned, and improvements to the Databricks environment

Requirements

What you’ll need

Working SQL ability, including joins, aggregations, query debugging, and resolving data issues within queries, notebooks, and jobs
Functional Python experience; ability to navigate existing scripts and workflows and implement solutions with the help of AI
Foundational database management concepts, including keys, grains, and normalization
Strong analytical judgment and experience in a real-world business setting
Demonstrated experience working with ambiguity to drive measurable stakeholder outcomes
Strong verbal and written communication skills across technical and non-technical stakeholder cohorts
Prior experience in a data engineering and/or analytics environment alongside others
Databricks, Snowflake, or other cloud data platform knowledge and experience
Confidence with technical documentation and project management within an engineering framework
Knowledge of data transformation tools and confidence with AI tooling in an analytics workflow
Full-time availability, 40 hours per week, Monday through Friday
Ability to participate in a co-op running January 2027 through June 2027, with flexibility for academic schedules

Benefits

Comp & perks

Full-time co-op experience, 40 hours per week, Monday through Friday
Opportunity for hands-on, real-world exposure
Opportunity to make material impact on strategy and business outcomes
Room to recommend and try better approaches
Equal opportunity employer supporting a diverse and inclusive workforce