Lead Data Engineer

CampusWorks, Inc.

Data Engineer building a federated data platform for higher education using Azure Databricks. Collaborating on data pipelines and transformation logic for institutional analytics.

Posted 7/30/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining batch data pipelines, with a strong focus on data quality, reliability, and performance. Proficient in orchestrating workflows and mentoring teams in a collaborative environment.

Highest-signal resume keywords

Apache SparkPythonSQLDatabricks WorkflowsAzure Data Factory

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Transformation LogicMedallion Architecture DesignData IntegrationData Quality Checks

Soft Skills

Problem-SolvingCommunicationCollaborationMentoringTechnical Leadership

Tools & Technologies

DatabricksAzure Data FactoryWorkdayBatch Pipeline Orchestration

Industry Keywords

Data GovernanceMulti-Tenant EnvironmentERP IntegrationSIS Integration

Tech Stack

Tools & technologies

ApacheAzureERPPythonSparkSQL

About the role

Key responsibilities & impact

Build and maintain batch data pipelines that ingest from Workday (HCM, Finance, Student) and legacy source systems into the Bronze layer
Develop transformation logic across Bronze / Silver / Gold layers using Spark, Python, and SQL on Databricks
Model data for analytics consumption, balancing performance, reliability, and maintainability
Orchestrate and schedule workloads (e.g., Databricks Workflows, Azure Data Factory, or Fabric pipelines) and monitor them for reliability
Implement data-quality checks and validation within pipelines
Serve as senior technical lead on complex integrations and cross-institution data workstreams (Lead Data Engineer)
Define and enforce engineering standards, patterns, and best practices
Mentor and provide technical guidance and code review to other engineers

Requirements

What you’ll need

Data Engineer: 3–6 years building production data pipelines
Lead Data Engineer: 7–10 years, with demonstrated technical leadership
Hands-on expertise with Apache Spark, Python, and SQL in a Databricks environment
Experience designing and building medallion or layered data architectures (Bronze / Silver / Gold or equivalent)
Proven experience integrating data from multiple ERP / SIS / operational source systems into an analytics platform
Experience with batch pipeline orchestration and scheduling (Databricks Workflows, Azure Data Factory, or similar)
Working understanding of data governance, security, and access concepts in a shared or multi-tenant environment
Strong problem-solving skills with a consistent focus on data quality and reliability
Excellent communication and collaboration skills on a remote team
Bachelor’s degree in a technical field or equivalent practical experience

Benefits

Comp & perks

Competitive pay
Robust benefits for full-time employees
Professional development opportunities
Flexibility for work-life balance
Charitable fundraising initiatives