Job Description:

Job Summary: The Senior Data Engineer is responsible for designing, building, and evolving Penn Mutual’s enterprise data platforms and pipelines that enable analytics, reporting, and data-driven decision making. 

As a senior individual contributor, the Senior Data Engineer partners closely with architecture, analytics, data governance, and application teams to translate business and analytical needs into robust data engineering solutions aligned with enterprise cloud and technology standards.

Responsibilities:

• 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.

Minimum Qualifications: To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the minimum knowledge, skill, and/or ability required.

• 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.

Preferred:

• Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
• Knowledge of Infrastructure as a Service concepts and tooling (Cloud Formation, Terraform, etc.), deployment automation tools (Jenkins, GitHub Actions, Bamboo, etc.)
• Knowledge of software development methodologies such as Agile or Scrum.

Competencies:

• Customer Service: Exceptional attitude and a passion for providing outstanding service to internal customers.
• Attention to Detail: Thoroughness in accomplishing a task through concern for all the areas involved, no matter how small. Monitors and checks work or information and plans and organizes time and resources efficiently
• Analytical Skills: Collects and researches data; Designs workflows and procedures; Identifies data relationships and dependencies.
• Communications: Exhibits good listening and comprehension. Expresses ideas and thoughts in verbal and written form. Keeps others adequately informed. Selects and uses appropriate communication methods. 
• Problem Solving: Ability to solve issues efficiently and quickly. 

Base Salary Range - $130,000 - $150,000

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 instill the confidence and reliability that comes from a stronger financial future. Penn Mutual and its affiliates offer a comprehensive suite of competitive products and services 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.

Penn Mutual is committed to Equal Employment Opportunity (EEO). We provide employment and advancement opportunities to all qualified applicants and associates, according to applicable laws. This is reflected in our practices for hiring, placement, promotion, transfer, demotion, layoff, termination, recruitment, compensation, selection or training, and all other terms and conditions of employment. All employment-related decisions and practices are free from unlawful discrimination. This includes: race, creed, color, national origin, ancestry, citizenship age, gender (including pregnancy), sexual orientation, gender identity or expression, domestic partnership or civil union status, marital status, genetic information, disability, religious observance or practice, liability, veteran status or any other classification protected under applicable law.