Edtech.com's Summary

Risepoint is hiring a Senior Data Engineer specialized in Databricks. This role involves building scalable data pipelines, optimizing Spark workflows, and collaborating with data teams to deliver cloud-based data solutions that support AI and machine learning initiatives.

Highlights

Build and maintain scalable data pipelines using Apache Spark on Databricks.
Develop ELT/ETL workflows integrating AWS and Azure cloud services.
Optimize Spark jobs for performance and cost efficiency.
Implement data quality, lineage, and compliance using Unity Catalog, Delta Lake, and AWS Lake Formation.
Collaborate with data scientists and ML engineers to support AI/ML projects.
Execute complex queries with Databricks SQL and develop transformations using PySpark and SQL.
Implement CI/CD pipelines for Databricks jobs utilizing GitHub Actions, Azure DevOps, or Jenkins.
Require 5+ years in software/data engineering with at least 2 years using Databricks and Apache Spark, strong Python, SQL, PySpark, and cloud expertise.
Bachelor’s degree in computer science, engineering, or related field.
Comprehensive benefits including paid PTO, medical options, retirement plan, parental leave, and professional development programs.

Senior Data Engineer- Databricks Full Description

Senior Data Engineer- Databricks

US - Remote

Full time

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 initiatives—especially those tied to AI-driven solutions and projects—by 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.

Original Job Description

Senior Data Engineer- Databricks

US - Remote

Full time

About the Role

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 initiatives—especially those tied to AI-driven solutions and projects—by 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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