Lead Data Engineer

Company OverviewWhat makes Harbor unique is our commitment to only partnering with the very best asset managers globally. This focus allows us to act in the best interests of our shareholders every day, and help them achieve their investment goals through active, cost-aware investing. This approach has served us well, becoming one of the largest and most highly regarded managers in the industry. We take a similar approach with the people we hire, seeking the very best individuals that share our passion for putting shareholders first, and we are currently looking to grow our firm with talented, intellectually diverse people with excellent work ethics. If you are passionate about putting shareholders first and enjoy the unique nature of working with the very best asset managers in the world, please visit us at harborcapital.com/careers, search for this position and click on "Apply" to start your application!Role DescriptionWe are seeking a Lead Data Engineer to drive the design, architecture, and delivery of scalable data platforms, AI-powered data products, and enterprise-grade data services. This role goes beyond hands-on engineering to include technical leadership, architectural decision-making, and cross-functional influence across the organization.You will lead the development of end-to-end data ecosystems—including data pipelines, storage, APIs, and AI-enabled services—leveraging modern cloud infrastructure and emerging AI/LLM capabilities. You will play a critical role in shaping how data is transformed into actionable insights and production-grade tools that directly support investment decisions and client outcomes.In addition to building, you will mentor engineers, set technical standards, and guide the evolution of our data platform, ensuring scalability, reliability, and alignment with long-term business strategy.You will partner closely with teams across Multi-Asset Solutions, Investment Research, Investment Products, Accounting, Marketing, and Distribution to translate complex business needs into robust, high-impact data solutions.Why would you want to work on our team?You will operate at the intersection of data engineering, AI innovation, and investment decision-making, with a high degree of ownership and visibility. This is a role where you will:Influence technical direction and architecture of a growing data platformBuild AI-powered data products used directly by investors and business leadersWork in a lean, high-impact team with minimal bureaucracyHave a clear line of sight between your work and real business outcomesHelp define best practices in a modern, cloud-native, AI-enabled environmentWho will thrive in this role?This role is ideal for engineers who:Think beyond implementation and design systems and platformsEnjoy mentoring others and leading technical discussionsBalance hands-on coding with strategic thinkingAre comfortable navigating ambiguity and shaping solutions from early-stage ideasTake ownership not just of features, but of systems, standards, and outcomesKey ResponsibilitiesLead the architecture, design, and implementation of scalable data platforms and AI-enabled data productsDefine and enforce data engineering standards, best practices, and design patternsOwn the end-to-end lifecycle of data pipelines, data services, and APIs from concept through productionDrive adoption of AI/LLM capabilities within data workflows and productsPartner with business stakeholders to translate complex requirements into technical solutionsMentor and guide engineers, providing technical leadership and code reviewsImprove system reliability, observability, and performance across the data stackLead technical decision-making on tools, frameworks, and architectureEnsure data governance, security, and compliance standards are embedded into systemsCollaborate across teams and contribute across the stack when neededKey Behavioral ExpectationsApplies emerging AI/LLM capabilities pragmatically, with curiosity and good judgmentComfortable with discovery work: prototype, test, iterate, and validate before scalingAdapts quickly as requirements and technical approaches evolveOwns delivery end-to-end, driving work through production and refinementCommunicates openly, contributes to design discussions, and challenges assumptions constructivelyCollaborates across teams and works across the stack when neededTechnical Knowledge, Skills & AbilitiesCore Requirements:Deep expertise in data engineering fundamentals (Python, SQL) with production experience Proven experience designing scalable, reliable data architectures and pipelines Strong experience with AWS cloud ecosystem (infrastructure, CI/CD, observability) Hands-on experience with AI-enabled applications and data pipelines Strong experience with Snowflake (including Cortex AI) or similar platforms Expertise in DevOps, containerization (Docker), and CI/CD pipelines Strong knowledge of database systems (Postgres, Aurora, or similar) Experience with Infrastructure as Code (CloudFormation, Pulumi; Terraform a plus) Experience integrating and leveraging LLM developer tools (Claude Code, Copilot, etc.) Nice to Have:Experience leading or mentoring engineering teams Experience in financial services or regulated environments Knowledge of data governance, lineage, and security frameworks Experience designing data products or internal platforms Familiarity with front-end or full-stack development for end-to-end ownershipEducational Qualifications & ExperienceBachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field (quantitative disciplines also welcome)10+ years of experience in Data Engineering, Software Engineering, or related fields2–4+ years of experience leading projects or teams (formal or informal leadership)Experience delivering production-grade data platforms or AI-enabled systemsFinancial services experience is a plus but not requiredCompensation Pay Range: This position offers a competitive base salary range of $180,000–$200,000, commensurate with experience and qualifications.This position is a hybrid opportunity based in our Chicago office. #LI-HybridSummaryLocation: Chicago OfficeType: Full time