Principal Software Architect

About the role

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions. At FactSet, our values are the foundation of everything we do. We are looking for an experienced Principal Software Architect to join our Data Solutions organization to shape and drive the technical vision for our expanding Data Platform. The role provides architectural leadership across infrastructure teams working on storage and access, transparency and orchestration, and data collection and acquisition tooling. The Data Platform is the foundation of FactSet's data offerings, serving critical data products to clients and internal consumers at scale. Our architecture spans modern cloud-based infrastructure, data lakehouse technologies, and orchestration frameworks that power thousands of data pipelines. As we evolve our platform to meet growing demands and embrace AI-driven capabilities, we need architectural leadership to ensure cohesion, scalability, and alignment with enterprise strategy.

What you’ll do

• Collaborate with fellow architects across Commercial Data to develop, document, and maintain our future state architecture for the data platform.
• Provide technical guidance and architectural oversight for key strategic initiatives across storage and access, orchestration, and data acquisition domains.
• Partner with execution teams to provide architectural support, bridging the gap between strategy and implementation where teams need guidance.
• Work closely with Enterprise Architecture to ensure Commercial Data's technical strategy aligns with FactSet's broader architectural vision and standards.
• Lead the development and review of Architecture Decision Records (ADRs) across the organization, establishing patterns and standards for technical decision-making.
• Champion the growth of technical talent by advocating for individual engineers, identifying skill gaps, and bringing outside expertise to elevate team capabilities.
• Stay current with industry trends in data engineering, data lakehouse architectures, orchestration, and AI/ML technologies, bringing relevant innovations to FactSet.
• Drive the architectural vision for an AI-driven future for data access at FactSet, incorporating LLMs and generative AI into our data platform capabilities.
• Establish and promote architectural patterns for data governance, metadata management, and semantic layers across the Commercial Data platform.
• Lead technical design reviews and provide mentorship to senior engineers and technical leads across multiple teams.
• Influence technology selection decisions and evaluation of new tools and platforms that align with our strategic direction.
• Foster a culture of technical excellence, encouraging teams to balance innovation with pragmatic, maintainable solutions.

What you’ll bring

• 10+ years of software engineering experience with deep expertise in data engineering, data platforms, and data infrastructure.
• Proven track record as a software architect or principal engineer designing large-scale data systems and platforms.
• Extensive hands-on experience with ETL/ELT systems, data pipeline orchestration tools (Apache Airflow, Prefect, Dagster, or similar).
• Strong experience with cloud infrastructure, particularly AWS services (S3, Glue, EMR, Lambda, Step Functions, EventBridge, etc.).
• Deep understanding of data lakehouse architectures and experience with platforms like Databricks or Snowflake.
• Proficiency in Python and relevant data engineering libraries for building production data systems.
• Demonstrated ability to develop and communicate architectural vision and translate strategy into actionable technical roadmaps.
• Experience creating Architecture Decision Records (ADRs) and establishing architectural governance practices.
• Strong collaboration skills with the ability to influence and align diverse stakeholders across technical and business organizations.
• Track record of mentoring senior engineers and growing technical capabilities within teams.
• Understanding of data governance principles, metadata management, and data quality frameworks.
• Ability to balance strategic long-term thinking with pragmatic near-term execution needs.

Nice to have

• Hands-on experience with the Databricks platform, including Delta Lake, Unity Catalog, and Databricks workflows.
• Experience architecting systems that incorporate AI/ML capabilities, particularly LLMs and generative AI for data access and discovery.
• Familiarity with semantic layer technologies and knowledge graph architectures.
• Background in metadata management platforms and data catalog solutions.
• Experience with streaming data architectures using Kafka, Kinesis, or similar platforms.
• Understanding of modern data governance frameworks and data privacy regulations.
• Experience with Apache Iceberg, Delta Lake, or other open table formats in production environments.
• Knowledge of vector databases and RAG (Retrieval-Augmented Generation) patterns for AI applications.
• Familiarity with DataOps practices and platform engineering approaches for data infrastructure.
• Experience working in financial services or with market data systems.
• Track record of speaking at conferences, contributing to open source, or thought leadership in the data engineering community.
• Experience with FinOps practices and cost optimization for cloud data platforms.
• Understanding of data mesh or data fabric architectural patterns.
• Certifications in AWS, Databricks, or related technologies.

Skills

Benefits

• Health, life, and disability insurance
• Retirement savings plans and discounted employee stock purchase program
• Paid time off for holidays, family leave, and company-wide wellness days
• Flexible work accommodations
• Career progression planning with dedicated time each month for learning and development
• Business Resource Groups open to all employees