Senior Data Engineer

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🔥 2 minutes ago

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Logo of Penn Mutual

Penn Mutual

1001 - 5000 employees

Founded 1847

For over 175 years, Penn Mutual has empowered individuals, families and businesses on the journey to achieve their financial goals. Through our partnership with Financial Professionals across the U.S., we help generations grow stronger by instilling the confidence and reliability that comes from a secure financial future. Penn Mutual and its affiliates offer a comprehensive suite of competitive and robust solutions to meet the unique needs of Financial Professionals and their clients, including life insurance, annuities, wealth management and institutional asset management. To learn more, including current financial strength ratings, visit www.pennmutual.com.

📋 Description

• 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

• 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

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

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