Principal Data Engineer

Everfi

. Own the design, architecture, and implementation of complex data engineering initiatives .

Posted 10/13/2026full-timeRemote • United StatesLead💰 $160,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in data engineering, focusing on the design and implementation of scalable data pipelines and platforms. Proficient in cloud data platforms and advanced data architecture, with a strong emphasis on mentoring and communication across technical and non-technical teams.

Highest-signal resume keywords

Data Engineering ExperienceData Architecture ExpertiseCloud Data Platforms (AWS, GCP, Azure)Advanced Python and SQL SkillsMentoring and Coaching

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignPlatform EngineeringBatch/Streaming SystemsData Warehouse ArchitectureData Lakehouse ArchitectureAirflowSparkDbtSnowflakeSQL

Soft Skills

Clear CommunicationCoaching MindsetCollaboration

Tools & Technologies

DatabricksRedshiftBigQuerySnowpark

Certifications & Qualifications

Dbt Certified DeveloperSnowPro CertificationApache Airflow Certification

Industry Keywords

Data Engineering StandardsArchitectural PatternsData Quality IssuesScalability ConstraintsReliability Gaps

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudGoogle Cloud PlatformJavaPythonScalaSparkSQL

About the role

Key responsibilities & impact

Own the design, architecture, and implementation of complex data engineering initiatives
Develop advanced data pipelines and data platform architecture with significant product or business impact
Identify and solve scalability constraints, data quality issues, architectural debt, and reliability gaps
Evaluate and recommend data engineering technologies, tools, cloud services, orchestration frameworks, and transformation tooling
Mentor data engineers through code review, architectural guidance, and hands-on coaching
Define and document data engineering standards, architectural patterns, and best practices
Participate in architecture discussions, design reviews, and pull request feedback
Partner with product, analytics, and operations stakeholders on complex data initiatives
Represent data engineering in cross-functional planning conversations
Communicate technical concepts and architectural trade-offs to technical and non-technical stakeholders
Evaluate emerging tools, frameworks, and architectural approaches
Conduct proof-of-concept work and provide recommendations
Share technical learning with the team

Requirements

What you’ll need

7–10+ years of data engineering experience
Track record of building complex, production-grade pipelines and platforms at scale
Deep expertise in data architecture, pipeline design, and platform engineering
Experience with batch/streaming systems, data warehouse and lakehouse architectures
Experience with Airflow, Spark, dbt, or Databricks
Strong proficiency in cloud data platforms: AWS, GCP, or Azure
Experience with Snowflake, Redshift, or BigQuery
Advanced skills in Python and SQL
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Snowpark and Snowflake ML/AI experience is a plus
Proficiency in Scala or Java is a plus
Coaching mindset and interest in mentoring engineers
Clear, confident communication with technical and non-technical audiences
dbt Certified Developer preferred
SnowPro Certification or advanced Snowflake certifications preferred
Experience with or certification in Apache Airflow preferred

Benefits

Comp & perks

Corporate Bonus Plan eligibility
100% remote position
Health insurance
Dental insurance
Vision insurance
401(k) with matching contribution
Flexible Paid Time Off (PTO)