Software Engineering Lead Data Engineer

MFS • Boston, MA

23h • Hybrid

About The Position

At MFS, you will find a culture that supports you in doing what you do best. Our employees work together to reach better outcomes, favoring the strongest idea over the strongest individual. We put people first and demonstrate care and compassion for our community and each other. Because what we do matters – to us as valued professionals and to the millions of people and institutions who rely on us to help them build more secure and prosperous futures.
THE ROLE In conjunction with the Enterprise Data Management Office, the Lead Data Engineer contributes to a long-term strategic initiative to unify and harmonize our investment data. This initiative enables enhanced investment decision making, risk management and client reporting for our multi-asset platform by delivering consistent, timely, accurate and user-friendly data to investors, risk teams and clients. Are you a hands-on and detailed-oriented individual working on the cutting edge of financial instruments, investment data, and analytics? Are you interested in investment data strategies across a wide variety of traditional and alternative asset classes? Are you a thinker who enjoys devising innovative and flexible business solutions to meet emerging business needs? The MFS Enterprise Data Management Office is actively searching for a Lead Data Engineer to implement data engineering and analytics solutions. Primary responsibilities include full implementation and maintenance of data ingestion, data maintenance, data validation and data delivery of investment data. We are looking for someone who thrives in an agile, collaborative, team-based environment, working closely with technology peers across MFS, investment professionals and key vendor partners. This position offers the opportunity to shape the future of investment data at MFS.

Requirements

• Bachelor’s degree in Computer Science or related disciplines.
• 5-6+ years of experience in design, development, and building data-oriented complex applications.
• Minimum of 2-4 years of hands-on progressive experience from SQL to Advanced SQL.
• Strong experience developing and maintaining data models in dbt (Data Build Tool) with at least a couple of years of hands-on experience.
• Experience managing dbt transformation workflows and implementing scalable modular design patterns.
• Experience working in data integration (ETL/ELT), data warehouse, and data analytics architecture with a sound understanding of design principles.
• Development experience in cloud-based PAAS platforms such as Microsoft Azure, Google GCP, or Amazon AWS.
• Deep understanding of Agile SDLC, DevOps, and cloud technologies, in addition to exposure to multiple diverse technologies, platforms, and processing environments.
• Knowledge of architectures and patterns such as unified data management architecture (UDM), data mesh architecture, event-driven architecture, real-time data flows, non-relational repositories, and data virtualization.
• Strong interpersonal and communication skills with the ability to lead cross-team collaboration and partnerships across a variety of internal and external constituencies.
• Demonstrated ability to contribute to strategic architecture initiatives and enterprise data standards alignment.
• Applicants must be currently authorized to work in the United States on a full-time basis. This position is not eligible for sponsorship.

Nice To Haves

• Knowledge of and experience with Snowflake and other cloud-native databases is highly preferred.
• Experience building solutions in the financial services domain with an understanding of financial instruments, transactions, and positions is desired.
• Experience working within the asset management industry and investment data domain, with exposure to multi-asset investment platforms and related data ecosystems.
• Understanding of asset management concepts and knowledge of various financial instruments and products, including traditional and alternative asset classes.
• Industry certifications in Snowflake, dbt, cloud data engineering platforms, data warehousing technologies, or financial markets/investment operations are highly valued.
• Demonstrated interest in emerging AI technologies and an understanding of how AI-driven tools can improve engineering processes, data quality, operational efficiency, and analytics workflows.
• Familiarity with leveraging AI-assisted development, automation, or data engineering best practices to enhance productivity and continuous improvement initiatives.

Responsibilities

• Design, develop, and implement data pipelines to maintain the unified data platform for the Enterprise Data Management Office.
• Create and maintain detailed technical design and architecture documentation to support development, implementation, and ongoing enhancement of data engineering solutions.
• Develop and execute comprehensive unit tests, ensuring thorough test coverage and clear documentation of test cases and results.
• Develop and maintain data models in dbt (Data Build Tool) within Snowflake, implementing business logic and ensuring alignment with existing architecture and enterprise data standards.
• Manage and contribute to dbt projects, ensuring code quality, proper documentation, and alignment with modular, scalable design patterns.
• Design, build, and administer scalable data pipelines and a robust data warehouse to support reporting, analytics, and operational use cases.
• Lead and participate in all development activities, developing and implementing solutions to meet business requirements aligned with strategic program objectives.
• Responsible for new and ongoing development of data pipelines sourcing from internal and external systems.
• Drive continuous improvement of data quality, resiliency, control, efficiency, monitoring, and operational reliability.
• Troubleshoot complex system interactions to identify and resolve root causes of issues.
• Partner with platform leads to design, develop, implement, and deploy new software components to the investment data platform.
• Partner with data architects to evaluate and finalize the unified data model.
• Partner with integration architects to upgrade and integrate data ingestion and data delivery tools with the unified data platform.
• Upgrade and integrate transformation tools, data validation tools, and orchestration tools with the unified data platform to implement data engineering, analytical engineering, and data maintenance capabilities.
• Support enterprise architecture alignment, scalable engineering governance, and modernization initiatives across the investment data platform.
• Leverage AI-assisted development practices, automation capabilities, and intelligent engineering tools to improve productivity, operational efficiency, and continuous improvement initiatives.
• Provide support during unexpected outages.

Benefits

• MFS contributes an amount equal to 15% of your base salary to your retirement account that is separate from the company -sponsored 401(k)
• Education Assistance: MFS contributes $100 monthly up to $10,000 lifetime maximum directly to loan provider
• Education Assistance: Tuition reimbursement up to $8,000 annually
• Education Assistance: Access to discounted tutors and college coaches
• Generous time off and fully paid leaves including 20-weeks for maternity, 12-weeks for parental and caregiver leaves
• Choice of medical and dental plans and an and an employer contribution into the Health Savings Account
• Tax deferred commuter benefits & flexible spending accounts (medical & dependent care)
• Wellness Programs: Robust wellness webinars, employee assistance program with a focus on mental health, subsidized fitness benefit via Wellhub (formerly Gympass), where you can workout at gyms, studios and boutique fitness locations near you, join virtual personal training sessions and access a wide variety of well-being apps

What This Job Offers

• Job Type: Full-time
• Career Level: Senior