Principal Data Engineer

Fitch Group • Chicago, IL

25d • $140,000 - $160,000 • Hybrid

About The Position

Fitch Group is seeking a Lead/Principal Data Engineer to join their Technology & Data Team in Chicago. This team is responsible for innovation and impact, leveraging cutting-edge technologies like AI and cloud solutions. The department includes various offices such as the Chief Data Office, Chief Software Office, Chief Technology Office, Emerging Technology, Shared Technology Services, Technology, Risk, and the Executive Program Management Office (EPMO). Fitch Group is a global financial information services provider with over 100 years of experience and a presence in over 30 countries. The company culture emphasizes credibility, independence, and transparency. Fitch Group includes Fitch Ratings, a major credit rating agency, and Fitch Solutions, a provider of insights, data, and analytics. Fitch Group is owned by Hearst and has dual headquarters in London and New York. The Technology & Data Team is recognized as a "Best Place to Work in Technology" by Built In for three consecutive years, offering a supportive environment for professional growth.

Requirements

• 8+ years of data engineering experience, including 3+ years in a lead role architecting large-scale data platforms.
• Expert-level proficiency in Java, Springboot for building cloud-native data processing solutions running on Docker/Kubernetes.
• Deep hands-on experience with Apache Airflow, Snowflake (data warehousing, modeling, optimization), and Databricks.
• Strong AWS expertise including S3, Lambda, Glue, EMR, Kinesis, EKS, RDS etc.
• Production database experience with PostgreSQL (design, optimization, replication) and MongoDB (document modeling, sharding, replica sets).
• Proven CI/CD and GitOps experience using GitHub, GitHub Actions, and ArgoCD for automated deployments and multi-environment management.
• Proficiency with agile tools such as JIRA for sprint management and Confluence for technical documentation and knowledge sharing.
• Excellent analytical, problem-solving, and communication skills, with the ability to explain complex concepts to non-technical stakeholders and drive initiatives in complex environments.
• Working knowledge of AI/ML frameworks (LangChain, LlamaIndex, AutoGen, etc.) and understand how Agentic AI can enhance data engineering workflows through automated data validation, intelligent orchestration, and self-healing pipelines.
• Practical understanding of AI integration patterns in data platforms, including prompt engineering, RAG architectures, and vector database implementations.
• Familiarity with Model Context Protocol (MCP) or similar frameworks for enabling AI agents to interact securely and efficiently with data sources, APIs, and tools.
• Experience with AI-powered development tools such as GitHub Copilot and Amazon Q.

Nice To Haves

• Experience with code quality metrics and shift-left principles.
• Experience testing container resiliency (Docker/Kubernetes).
• Experience designing large end-to-end performance scenarios.
• Experience building large and high-performing data pipelines.
• Exposure to Playwright and BDD for automated testing.
• Exposure to the financial industry and data platforms (data warehouses, data lakes).
• Experience with modern data stack tools, data mesh/fabric architectures, and streaming platforms (Kafka, Kinesis).
• Proficiency with observability tools (Datadog) and data quality/governance frameworks.
• Understanding of data security and compliance standards (GDPR, SOC 2, CCPA) and contributions to open-source data projects.
• Relevant certifications (AWS Data Analytics/Solutions Architect, Databricks/Snowflake Data Engineer, CKA).
• Hands-on experience building production Agentic AI systems that operate on data platforms, including multi-agent orchestration and intelligent pipeline optimization.
• Deep expertise with Model Context Protocol (MCP) implementation, including building custom MCP servers or integration patterns for enterprise data platforms.

Responsibilities

• Lead the design and architecture of end-to-end data pipelines and solutions on modern cloud-based platforms, including Snowflake, Databricks, and AWS.
• Lead the design and architecture of end-to-end data pipelines and solutions on platforms including Java, Springboot, Docker/Kubernetes, Snowflake, Databricks, and AWS.
• Design and implement data solutions using PostgreSQL for relational data and MongoDB for NoSQL requirements, ensuring optimal performance and scalability.
• Architect and deploy containerized data applications using Docker, Kubernetes, and AWS EKS, incorporating GitHub Actions for automated deployments.
• Design and implement CI/CD pipelines using GitHub Actions, establish branching strategies, and ensure automated testing, code quality checks, and security scanning.
• Collaborate with cross-functional teams—including Data Scientists, Analytics teams, and business stakeholders—to translate requirements into scalable technical solutions.
• Mentor and guide data engineers by promoting technical excellence, establishing coding standards, and conducting architecture reviews.
• Drive data platform modernization initiatives and ensure data quality, reliability, and governance across all data systems.
• Design and implement AI-enhanced data pipelines that leverage LLMs and Agentic AI frameworks to automate data quality checks, anomaly detection, and intelligent data transformation workflows.
• Architect data infrastructure to support AI/ML workloads, including feature stores, vector databases, and real-time inference pipelines integrated with cloud-native services.
• Leverage established standards and best practices to integrate AI agents into data engineering workflows, including context management protocols (MCP) for seamless AI-to-data-platform communication.

Benefits

• Hybrid Work Environment: On-site presence required two days per week.
• A Culture of Learning & Mobility: Access to dedicated training, leadership development, and mentorship programs to support continuous learning.
• Investing in Your Future: Retirement planning and tuition reimbursement programs to help you meet your short- and long-term goals.
• Promoting Health & Wellbeing: Comprehensive healthcare offerings that support physical, mental, financial, social, and occupational wellbeing.
• Supportive Parenting Policies: Family-friendly policies, including a generous global parental leave plan, designed to help you balance work and family life.
• Inclusive Work Environment: A collaborative workplace where all voices are valued, supported by Employee Resource Groups that unite and empower colleagues worldwide.
• Dedication to Giving Back: Paid volunteer days, matched donation programs, and ample opportunities to volunteer in your community.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed