Penn Mutual Logo

Penn Mutual

Staff Data Engineer

Reposted 12 Days Ago
Remote
Hiring Remotely in United States
145K-165K Annually
Senior level
Remote
Hiring Remotely in United States
145K-165K Annually
Senior level
The Staff Data Engineer designs and builds data platforms and pipelines, ensuring data integrity and collaboration across teams for analytics and reporting.
The summary above was generated by AI

Job Description:

 

The Staff Data Engineer is responsible for designing, building, and evolving Penn Mutual’s enterprise data platforms and pipelines that enable analytics, reporting, and datadriven decision making. This role provides senior technical leadership across data ingestion, transformation, storage, and consumption layers, ensuring data is reliable, scalable, secure, and wellgoverned.

As a senior individual contributor, the Staff 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 Penn Mutual’s Connected Data Strategy and following cloud and enterprise technology standards established by the Enterprise Architecture group.

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.
  • Serve as a technical leader and subject‑matter expert for data engineering practices across the organization.
  • Mentor junior and mid‑level data engineers through design reviews, code reviews, and knowledge sharing.
  • 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.
  • Demonstrates a commitment to AI fluency by embracing AI tools and technologies to enhance individual and team performance, decision-making, and innovation

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).
  • 10+ 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).
  • 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).
  • Experience with AWS serverless integration (e.g., Glue, Lambda, Step).
  • 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.
  • Previous experience in leading or mentoring junior engineers.

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. 
  • Managing People: Develops subordinates’ skills and encourages growth; provides direction and guidance; reacts well under pressure; motivates others to perform well and exhibits confidence in self and others.
  • Problem Solving: Ability to solve issues efficiently and quickly. 
  • Relationship Management: Manages interactions to service and support the organization; establishes credibility with all interactions.
  • Teamwork: Contributes to building a positive team spirit. Exhibits objectivity and openness to others' views.

Base Salary Range - $145,000 - $165,000

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.

Similar Jobs

2 Days Ago
Remote or Hybrid
United States
156K-263K Annually
Senior level
156K-263K Annually
Senior level
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
The Senior Staff Data Engineer will design scalable data systems, lead technical direction, optimize data platforms, and ensure data quality and performance for Observability & Insights.
Top Skills: AirflowAWSAzureCassandraDatadogDbtFlinkGCPGrafanaPrometheusSailpointSnowflakeSpark
8 Days Ago
In-Office or Remote
225K-290K Annually
Senior level
225K-290K Annually
Senior level
Blockchain • Fintech • Payments • Financial Services • Cryptocurrency • Web3
This role involves defining data reliability strategies, establishing company-wide standards for data quality, and leading cross-functional data engineering initiatives at Circle.
Top Skills: AIAirflowBigQueryDataplexDbtGoKubernetesPython
9 Days Ago
Remote or Hybrid
215K-250K Annually
Senior level
215K-250K Annually
Senior level
Artificial Intelligence • Fintech • Machine Learning • Mobile • Payments • Retail • Software
The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.
Top Skills: AWSDagsterDbtPythonSnowflakeSQL

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account