Lead Data Engineer

Long Ridge Partners; New York (NY); On-site; USD 175,000 - 225,000; Full time

Job summary

Long Ridge Partners is seeking a hands-on Senior/Lead Data Engineer to architect scalable, cloud-first data solutions. You’ll set engineering standards, lead small teams, and own end-to-end data initiatives supporting analytics and investment decision-making.

The role requires strong Python/SQL, Snowflake, and AWS experience, with opportunities to mentor engineers and collaborate with Analysts, Quants, and Portfolio Managers. NY/CA/IL-based applicants are considered.

Qualifications

• Significant experience building and operating production data platforms.
• Strong Python and SQL skills across relational and NoSQL systems.
• Deep experience with Snowflake or a comparable modern cloud data warehouse.

Responsibilities

• Lead the design and delivery of scalable ingestion pipelines, data models, and platform services using Python, SQL, Snowflake, and AWS.
• Architect reliable solutions for structured, unstructured, market, and alternative datasets with focus on performance and resilience.
• Drive evolution of the Data Acquisition Platform for onboarding, metadata generation, and AI-enabled workflows.

Skills

Python

SQL

Snowflake

AWS

Airflow

Data modeling

Leadership

Education

Bachelor's degree in CS/Math/Engineering

Job description

A leading global investment management firm is hiring a hands-on Senior/Lead Data Engineer to provide technical leadership for the platforms, pipelines, and data products that power analytics, applications, and investment decision-making across the firm.

You'll architect scalable, cloud-first data solutions, set engineering standards, and lead small teams through the delivery of reliable, analytics-ready datasets and services. It's a role that pairs deep technical execution with mentorship and cross-functional partnership, and it carries real ownership of complex data initiatives. There's a clear path into people-management responsibilities over time.

What You’ll Do

• Lead the design and delivery of scalable ingestion pipelines, data models, and platform services using Python, SQL, Snowflake, and AWS
• Architect reliable solutions for structured, unstructured, market, and alternative datasets, with a focus on performance, lineage, usability, and operational resilience
• Drive the evolution of the Data Acquisition Platform covering APIs, services, plugins, and AI-enabled workflows for onboarding, pipeline creation, metadata generation, and natural-language data access
• Build and improve automated data-quality frameworks covering completeness, freshness, schema integrity, reconciliations, and business-rule validation
• Own technical standards for testing, observability, alerting, incident response, and production support across a large and growing dataset estate
• Lead root-cause analysis on complex, time-sensitive data incidents and drive durable fixes
• Mentor engineers through design reviews, code reviews, pairing, and technical coaching, helping shape team practices and engineering culture
• Partner directly with Analysts, Quants, Portfolio Managers, and external data providers to turn requirements into robust end-to-end solutions
• Champion data engineering best practices and influence technical direction across partner teams
• Potentially manage a small team, including prioritization, delivery planning, feedback, and career development

What We’re Looking For

• Significant experience building and operating production data platforms, pipelines, and analytics-ready data products
• Strong Python and SQL skills, with experience across relational and NoSQL data systems
• Deep experience with Snowflake or a comparable modern cloud data warehouse
• Strong hands‑on experience with AWS data and cloud services, including designing secure, scalable, cost‑effective production architectures
• Experience designing and orchestrating production workflows with Airflow or comparable tools
• Cloud infrastructure experience in AWS, Azure, or Google Cloud
• Strong understanding of data modeling, large‑scale dataset performance, time‑series data, and temporal‑query patterns
• A track record of leading technical projects end‑to‑end, making sound architectural decisions, and improving complex existing systems
• Proven ability to mentor engineers and communicate effectively with both technical and business stakeholders
• Bachelor's degree in computer science, mathematics, engineering or a related field

Nice to Have

• Go and service-oriented platform development
• Applying AI/LLM capabilities to data engineering workflows
• Financial services or market data experience

Why Join?

You’ll work on data problems that directly support investment decisions, structured and unstructured, market and alternative, at meaningful scale and with real performance demands. The Data Acquisition Platform roadmap includes AI-enabled workflows for pipeline creation, metadata generation, and natural-language data access, so there's genuine greenfield work alongside the platform engineering.

The role carries broad ownership: you’ll set technical standards, make architectural calls, and see them through to production. You’ll also work shoulder-to-shoulder with Analysts, Quants, and Portfolio Managers, which means close proximity to the business rather than distance from it. For engineers who want to grow into technical or people leadership, the path here is explicit.

Compensation

For NY, CA, and IL-based applicants, the starting base pay range for this role is USD 175,000–225,000 annually. Actual base pay depends on several factors, including relevant experience, business needs, and market demands. This role may also be eligible for bonus compensation and employee benefits.