Senior Data Engineer

Penn Mutual

Senior Data Engineer designing, building, and evolving Penn Mutual’s enterprise data platforms and pipelines. Collaborating closely with teams to enable analytics, reporting, and data-driven decision making.

Posted 6/16/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $130,000 - $150,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudJavaPythonScalaSQL

About the role

Key responsibilities & impact

Design, build, and maintain scalable batch and streaming data pipelines supporting enterprise analytics, reporting, and downstream consumption
Develop and optimize data ingestion, transformation, and orchestration workflows across structured and semi‑structured data sources
Engineer and maintain curated, analytics‑ready data models (e.g., dimensional, canonical, or domain‑oriented datasets)
Ensure data solutions meet performance, reliability, availability, and recoverability expectations
Implement data solutions aligned to Penn Mutual’s cloud data platform strategy , including cloud storage, compute, and analytics services
Apply data architecture patterns that support data lakes, lake houses, and analytical warehouses
Partner with Enterprise Architecture to ensure data solutions conform to technology standards, integration patterns, and security requirements
Contribute to platform evolution decisions, including tooling selection, architectural patterns, and modernization initiatives
Embed data quality checks, validation rules, and observability into pipelines to ensure trusted data
Support data governance and stewardship practices , including metadata management, lineage, and controlled data access
Ensure data solutions comply with security, privacy, and regulatory requirements relevant to financial services and insurance
Collaborate with analytics, reporting, and data science teams to enable self‑service analytics and advanced insights
Translate business requirements into well‑designed data structures and datasets that are easy to consume and reuse
Support downstream use cases including dashboards, regulatory reporting, operational analytics, and advanced modeling
Promote engineering best practices including version control, automated testing, CI/CD, and documentation
Drive continuous improvement through evaluation of emerging data technologies and industry trends

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (Master’s degree preferred)
5+ years of professional experience in data engineering, analytics engineering, or data platform development
Strong proficiency in SQL and at least one modern programming language commonly used for data engineering (e.g., Python, Java, or Scala)
Develop AWS serverless solutions using Lambda, Glue, Step Functions, SNS/SQS, EMR, Lake Formation, API Gateway, IAM, CloudFormation, CloudWatch, S3
Extensive experience designing and building data pipelines and analytical data models
Hands‑on experience with cloud‑based data platforms and distributed data processing concepts
Solid understanding of data architecture patterns, data integration, and performance optimization
Strong problem‑solving skills with the ability to analyze complex data challenges and implement effective solutions
Excellent communication skills, with the ability to explain data concepts to both technical and non‑technical stakeholders.

Benefits

Comp & perks

Comprehensive suite of competitive products and services
Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringanalytics engineeringdata platform developmentSQLPythonJavaScaladata ingestiondata transformationdata orchestration

Soft Skills

problem-solvingcommunication