Senior Software Engineer - Python Data Engineer

Overview

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. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients’ needs and exceeding their expectations.

Your Team’s Impact

Are you an experienced hands-on data engineer ready to lead, design, and deliver business-critical data solutions? We’re seeking a Senior Python Data Engineer to design, build, and optimize robust ETL workflows, vendor onboarding and deprecation processes, and scalable data integration pipelines fueling our key data products (including the MVA and Third-Party Identifier systems).

You’ll independently own and execute engineering projects, often handling complex, multi-step work with evolving business requirements. Your technical expertise and communication skills will make you a go-to resource for the team—leading in technical architecture, process automation, documentation, problem solving, and mentorship.

What You’II Do

• Lead end-to-end design and delivery of efficient, fault-tolerant Python and SQL data pipelines for batch and streaming ingestion, transformation, and vendor onboarding.
• Drive complex, ambiguous projects: independently plan and execute multi-stage initiatives from discovery through implementation, including integrating new vendors/data, migrating legacy workflows, and automating deprecation logic.
• Own technical direction and design: produce clear architecture diagrams, process documentation, and hands-on technical reviews for new data workflow components and enhancements.
• Mentor and collaborate: act as a resource for peers, contribute to team knowledge sharing, and support onboarding, code reviews, and informal collaboration across teams and functions.
• Production support and reliability: diagnose and resolve job failures, resource bottlenecks, and data issues; implement fault-tolerance and graceful error-handling in production pipelines.
• Communicate with stakeholders: regularly update project status, share technical risks, and present findings to engineering leadership and non-technical partners.
• Automate operational processes: streamline onboarding of new data sources/types using CI/CD tools (e.g., GitHub Actions) and practice strong DevOps.
• Continually improve codebase: refactor large code segments, enhance unit test coverage, structure repeated logic, and set standards for maintainability.
  
  

• Minimum 7+ years hands-on development with Python in a data engineering or ETL environment.
• Deep knowledge of SQL for transforming and integrating large, complex datasets.
• Hands-on experience designing, building, and supporting scalable production ETL pipelines on Databricks (including Databricks notebooks, workflows Jobs, Delta Lake, and Spark on Databricks).
• Strong track record in delivering and leading complex projects with ambiguous or evolving requirements.
• Experience designing technical architecture, producing process documentation, and driving solution adoption across teams.
• Experience automating workflows, managing vendor feeds or external data integrations.
• Mandatory: Proven experience working with cloud platforms, specifically Databricks on AWS (EC2, S3, Lambda, and Databricks).
• Excellent debugging, troubleshooting, and production support (CPU/memory, bottlenecks, late jobs, unhealthy queues).
• Excellent communication—capable of explaining technical concepts to engineers and business partners alike, and producing high-quality written documentation.
• Practice in mentoring, team code reviews, and onboarding new engineers.
  
  

At FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means:

• The opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up.
• Support for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days.
• Flexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives.
• A global community dedicated to volunteerism and sustainability, where collaboration is always encouraged, and individuality drives solutions.
• Career progression planning with dedicated time each month for learning and development.
• Business Resource Groups open to all employees that serve as a catalyst for connection, growth, and belonging.
  
  

Salary is just one component of our compensation package and is based on several factors including but not limited to education, work experience, and certifications.

Company Overview

FactSet (NYSE:FDS | NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn.

At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law.