Senior Data Engineer

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Risepoint

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2007

📚 Education

🤝 B2B

Education • B2B

Risepoint is an education technology company that partners with regional public and private universities to design, launch, and grow workforce-focused online degree programs. It provides marketing, student support, faculty support, technology implementations, performance monitoring, and student ROI research to help institutions expand access, increase enrollments, and deliver high-return programs for working adults.

📋 Description

• Design, build, and own scalable data pipelines and dimensional models on Databricks (PySpark, SQL, medallion architecture) — delivering trusted, on-time data products and meeting SLAs within your assigned scope. • Ingest data from operational and SaaS sources such as Salesforce into the lakehouse, favoring managed connectors like Lakeflow Connect where appropriate. • Build and maintain Kimball-style dimensional models — facts, conformed dimensions, and slowly changing dimensions — as the analytics layer of record. • Develop, test, and document transformations in dbt (models, sources, snapshots, tests, exposures) with strong CI discipline. • Manage data assets in Unity Catalog, including catalogs, schemas, permissions, and lineage. • Optimize performance and cost through cluster and warehouse sizing, Spark tuning, partitioning, and tagging for cost attribution. • Operationalize machine learning workflows using MLflow for experiment tracking, model registry, and deployment, applying MLOps best practices. • Help coordinating day-to-day work with offshore vendor engineering resources — setting priorities, sequencing deliverables, and keeping their work aligned to sprint commitments and the platform roadmap. • Translate business and technical requirements into clear specifications, acceptance criteria, and design guidance that offshore teams can execute with minimal ambiguity. • Quality-check offshore deliverables through code review, testing, and validation against data standards, performance targets, and definition-of-done before changes are promoted to production. • Collaborates with data architects, analysts, and business stakeholders to keep data accurate and well-governed, building alignment within the team and with immediate cross-functional partners on delivery. • Uphold engineering standards, code review practices, and documentation conventions across both onshore and offshore contributors. • Support the team's growth by training and coaching engineers on tools, standards, and best practices as the platform scales.

🎯 Requirements

• 7+ years in data engineering on big data and cloud platforms, including 3+ years hands-on with Databricks (Spark/PySpark, Delta Lake, jobs). • Proven delivery of Kimball / dimensional data models in a modern warehouse or lakehouse, with strong SQL and Python (PySpark). • Production experience with dbt (models, tests, snapshots) and with Unity Catalog for governance, access control, and lineage. • Working knowledge of the ML lifecycle and MLOps, including MLflow for experiment tracking, model registry, and deployment. • Experience translating business and technical requirements into clear specifications and coordinating or overseeing offshore and vendor engineering resources, including reviewing their deliverables for quality. • Strong communication and stakeholder skills, with a track record of mentoring engineers and setting technical standards.

🏖️ Benefits

• Risepoint is an equal-opportunity employer and supports a diverse and inclusive workforce.