Software Engineering Lead Data Engineer

mfs; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

MFS is seeking a Lead Data Engineer to design, build, and maintain a unified data platform for the Enterprise Data Management Office. You will lead ingestion, validation, and delivery of investment data across a multi-asset platform, collaborating with technology peers, investment professionals, and vendor partners.

You will work in an agile environment, develop dbt models in Snowflake, implement scalable data pipelines, and support reporting and risk management initiatives across the investment

Qualifications

• Bachelor's degree in Computer Science or related disciplines.
• 5-6+ years of experience in design, development, and building data-oriented complex applications.
• 2-4 years of hands-on experience with SQL and advanced SQL.
• Hands-on experience with dbt and data modeling in Snowflake.
• Experience in data integration (ETL/ELT) and cloud-based PAAS platforms (Azure, AWS, GCP).

Responsibilities

• Design, build, and maintain data pipelines for the unified data platform.
• Create and maintain technical design and architecture documentation.
• Develop and execute unit tests and document test results.
• Develop and maintain data models in dbt within Snowflake.
• Manage dbt projects and ensure code quality and modular design.
• Lead development activities to meet business requirements and program objectives.
• Develop data pipelines sourcing from internal and external systems.
• Improve data quality, resiliency, and operational reliability.
• Troubleshoot complex system interactions and resolve root causes.
• Collaborate with platform, data architects, and integration teams.

Skills

Data pipelines

dbt

Snowflake

SQL

ETL/ELT

Cloud platforms

Azure

GCP

AWS

Data modeling

Education

Bachelor's degree in Computer Science

Tools

Snowflake

dbt

Job description

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.

WHAT YOU WILL DO

• 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.

WHAT WE ARE LOOKING FOR

• 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. Knowledge of and experience with Snowflake and other cloud-native databases is highly preferred.
• Development experience in cloud-based PAAS platforms such as Microsoft Azure, Google GCP, or Amazon AWS.
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