Lead Data Engineer
Harbor Capital Advisors, Inc., Chicago, IL, United States
Company Overview
What 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. It has helped us become one of the largest and most highly regarded managers in the industry. We take the same approach with the people we hire, seeking the very best individuals who share our passion for putting shareholders first and who possess excellent work ethics.
Role Description
We 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 You Would 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 platform
Build AI‑powered data products used directly by investors and business leaders
Work in a lean, high‑impact team with minimal bureaucracy
Have a clear line of sight between your work and real business outcomes
Help define best practices in a modern, cloud‑native, AI‑enabled environment
Who Will Thrive in This Role?
This role is ideal for engineers who:
Think beyond implementation and design systems and platforms
Enjoy mentoring others and leading technical discussions
Balance hands‑on coding with strategic thinking
Are comfortable navigating ambiguity and shaping solutions from early‑stage ideas
Take ownership not just of features, but of systems, standards, and outcomes
Key Responsibilities
Lead the architecture, design, and implementation of scalable data platforms and AI‑enabled data products
Define and enforce data engineering standards, best practices, and design patterns
Own the end‑to‑end lifecycle of data pipelines, data services, and APIs from concept through production
Drive adoption of AI/LLM capabilities within data workflows and products
Partner with business stakeholders to translate complex requirements into technical solutions
Mentor and guide engineers, providing technical leadership and code reviews
Improve system reliability, observability, and performance across the data stack
Lead technical decision‑making on tools, frameworks, and architecture
Ensure data governance, security, and compliance standards are embedded into systems
Collaborate across teams and contribute across the stack when needed
Key Behavioral Expectations
Apply emerging AI/LLM capabilities pragmatically, with curiosity and good judgment
Comfortable with discovery work: prototype, test, iterate, and validate before scaling
Adapt quickly as requirements and technical approaches evolveOwn delivery end‑to‑end, driving work through production and refinement
Communicate openly, contribute to design discussions, and challenge assumptions constructively
Collaborate across teams and work across the stack when needed
Technical Knowledge, Skills & Abilities
Core 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 ownership
Educational Qualifications & Experience
Bachelor’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 fields
2–4+ years of experience leading projects or teams (formal or informal leadership)
Experience delivering production‑grade data platforms or AI‑enabled systems
Financial services experience is a plus but not required
Compensation Pay Range
This position offers a competitive base salary range of $180,000–$200,000, commensurate with experience and qualifications.
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What 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. It has helped us become one of the largest and most highly regarded managers in the industry. We take the same approach with the people we hire, seeking the very best individuals who share our passion for putting shareholders first and who possess excellent work ethics.
Role Description
We 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 You Would 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 platform
Build AI‑powered data products used directly by investors and business leaders
Work in a lean, high‑impact team with minimal bureaucracy
Have a clear line of sight between your work and real business outcomes
Help define best practices in a modern, cloud‑native, AI‑enabled environment
Who Will Thrive in This Role?
This role is ideal for engineers who:
Think beyond implementation and design systems and platforms
Enjoy mentoring others and leading technical discussions
Balance hands‑on coding with strategic thinking
Are comfortable navigating ambiguity and shaping solutions from early‑stage ideas
Take ownership not just of features, but of systems, standards, and outcomes
Key Responsibilities
Lead the architecture, design, and implementation of scalable data platforms and AI‑enabled data products
Define and enforce data engineering standards, best practices, and design patterns
Own the end‑to‑end lifecycle of data pipelines, data services, and APIs from concept through production
Drive adoption of AI/LLM capabilities within data workflows and products
Partner with business stakeholders to translate complex requirements into technical solutions
Mentor and guide engineers, providing technical leadership and code reviews
Improve system reliability, observability, and performance across the data stack
Lead technical decision‑making on tools, frameworks, and architecture
Ensure data governance, security, and compliance standards are embedded into systems
Collaborate across teams and contribute across the stack when needed
Key Behavioral Expectations
Apply emerging AI/LLM capabilities pragmatically, with curiosity and good judgment
Comfortable with discovery work: prototype, test, iterate, and validate before scaling
Adapt quickly as requirements and technical approaches evolveOwn delivery end‑to‑end, driving work through production and refinement
Communicate openly, contribute to design discussions, and challenge assumptions constructively
Collaborate across teams and work across the stack when needed
Technical Knowledge, Skills & Abilities
Core 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 ownership
Educational Qualifications & Experience
Bachelor’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 fields
2–4+ years of experience leading projects or teams (formal or informal leadership)
Experience delivering production‑grade data platforms or AI‑enabled systems
Financial services experience is a plus but not required
Compensation Pay Range
This position offers a competitive base salary range of $180,000–$200,000, commensurate with experience and qualifications.
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