Risepoint
Senior Data Engineer- Databricks
🇺🇸 Remote - US
🕑 Full-Time
💰 TBD
💻 Data Science
🗓️ November 19th, 2025
Edtech.com's Summary
- Build scalable data pipelines using Databricks, Apache Spark, PySpark, and SQL.
- Design and deliver cloud-native data solutions integrating AWS and Azure services.
- Optimize Spark jobs for performance and cost within cloud infrastructure.
- Support AI and machine learning workflows including data preparation and model operationalization.
- Implement CI/CD pipelines for Databricks jobs with GitHub Actions, Azure DevOps, or Jenkins.
- Ensure data quality, lineage, and compliance using Unity Catalog, Delta Lake, and AWS Lake Formation.
- Bachelor's degree in computer science, engineering, or related field required.
- Minimum 5 years in software/data engineering with at least 2 years of experience on Databricks and Apache Spark.
- Strong proficiency in Python, SQL, PySpark, and deep knowledge of AWS and Azure cloud services.
- Experience with infrastructure-as-code tools like Terraform or CloudFormation is preferred.
Senior Data Engineer- Databricks Full Description
Risepoint assists primarily regional universities in increasing their access and impact by making their academic programs available to students online. Founded in 2007, Risepoint's mission is to expand access to high-quality, affordable, and workforce-relevant education, especially for working and adult students. Risepoint brings single-minded dedication to student success, an integrated set of services, and data-driven performance to our collaboration with university partners.
About the Role
We're looking for a hands-on Data Engineer to build reliable, scalable data pipelines on Databricks. You'll turn requirements into production-grade ELT/ETL jobs, Delta Lake tables, and reusable components that speed up our teams. In this role, you'll implement and improve reference patterns, optimize Spark for performance and cost, apply best practices with Unity Catalog and workflow orchestration, and ship high-quality code others can build on. If you love solving data problems at scale and empowering teammates through clean, well-documented solutions, you'll thrive here.
Key Responsibilities
- The ideal candidate will have a strong background in building scalable data pipelines, optimizing big data workflows, and integrating Databricks with cloud services
- This role will play a pivotal part in enabling the customer's data engineering and analytics initiativesâespecially those tied to AI-driven solutions and projectsâby implementing cloud-native architectures that fuel innovation and sustainability
- Partner directly with the customer's data engineering team to design and deliver scalable, cloud-based data solutions
- Execute complex ad-hoc queries using Databricks SQL to explore large lakehouse datasets and uncover actionable insights
- Leverage Databricks notebooks to develop robust data transformation workflows using PySpark and SQL
- Design, develop, and maintain scalable data pipelines using Apache Spark on Databricks
- Build ETL/ELT workflows with AWS and Azure Services
- Optimize Spark jobs for both performance and cost within the customer's cloud infrastructure
- Collaborate with data scientists, ML engineers, and business analysts to support AI and machine learning use cases, including data preparation, feature engineering, and model operationalization
- Contribute to the development of AI-powered solutions that improve operational efficiency, route optimization, and predictive maintenance in the waste management domain
- Implement CI/CD pipelines for Databricks jobs using GitHub Actions, Azure DevOps, or Jenkins
- Ensure data quality, lineage, and compliance through tools like Unity Catalog, Delta Lake, and AWS Lake Formation
- Troubleshoot and maintain production data pipelines
- Provide mentorship and share best practices with both internal and customer teams
Qualifications
- Bachelor's degree in computer science, Engineering, or a related field
- 5+ years of experience in software/data engineering, including at least 2 years working with Databricks and Apache Spark
- Strong proficiency in Python, SQL, and PySpark
- Deep understanding of AWS and Azure Cloud service
- Experience with Databricks Data LakeHouse, Databricks Workflows, and Databricks SQL, dbt
- Solid grasp of data Lakehouse and warehousing architecture
- Prior experience supporting AI/ML workflows, including training data pipelines and model deployment support
- Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
- Strong analytical and troubleshooting skills in a fast-paced, agile environment
- Excellent collaboration skills for interfacing with both technical and non-technical customer stakeholders
- Clear communicator with strong documentation habits
- Comfortable leading discussions, offering strategic input, and mentoring others
Risepoint offers the following comprehensive benefits:
- 18 days PTO + Winter Shutdown
- 12 designated holidays + 1 floating holiday
- Medical - four options
- Dental
- Vision
- Life & Disability (company paid)
- Flexible Spending Account & Health Savings Account
- Retirement plan with company match
- Maternity / Paternity / Parental Leave (company paid)
- Volunteer Time Off
Supplemental Benefits:
- Wellness program
- Alternative medicine options
- Pet discounts
- Accident, Critical Illness and Hospital Indemnity
Personal and Professional Development:
- Continuous Professional and Leadership Development Programs
- Tuition Reimbursement for employees and their dependents
- Rewards & Recognition programs
Risepoint is an equal-opportunity employer and supports a diverse and inclusive workforce.
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