Data Engineer

Data EngineerLocation: San Francisco, CA or New York, NYWork Model: OnsiteCompensation: $150,000 - $175,000 base + bonusAbout the CompanyThis organization is a technology-focused investment platform that partners with high-growth and enterprise software businesses to drive long-term value creation. Data, analytics, and technical diligence play a meaningful role in how the firm evaluates opportunities and supports portfolio performance.The team is investing heavily in modern data capabilities to improve how decisions are made "” combining engineering, analytics, and AI to build scalable internal systems that support analytical workflows and operational insights.The culture is highly collaborative, intellectually curious, and execution-focused. Teams work closely across technical and business functions, valuing ownership, problem-solving, and thoughtful engineering.About the RoleThis is a rare opportunity for an early-career Data Engineer to work at the intersection of data engineering, analytics, and applied AI in a highly analytical environment.You'll help build the data foundation powering internal AI systems, portfolio analytics, and strategic decision-making tools. This role offers meaningful ownership from day one "” combining hands-on engineering with analytical problem-solving across structured data, APIs, cloud infrastructure, and emerging AI workflows.You will work closely with both technical and commercial stakeholders, helping shape how data is collected, transformed, and operationalized to drive smarter decisions.Key ResponsibilitiesBuild and maintain production-grade data pipelines across internal systems, external data sources, APIs, and unstructured datasetsDesign and optimize ETL/ELT workflows that power analytics and AI-enabled applicationsImprove data quality, consistency, and reliability across business-critical datasetsPartner on data infrastructure, integrations, and architecture decisions to improve scalability and performanceDevelop analytics workflows, dashboards, and reporting solutions that surface actionable insightsSupport engineering improvements to internal analytical systems through automation and monitoringBuild and maintain API integrations and external data connectionsDocument data lineage, schemas, and technical architecture to improve transparency and maintainabilityProvide quantitative and technical support on high-priority analytical initiativesMust Haves2-4 years of experience in data engineering, analytics engineering, or a similar technical roleStrong proficiency in SQL and Python for data transformation, analysis, and automationExperience building and maintaining production data pipelinesHands-on experience with Snowflake or similar cloud data warehouse technologiesFamiliarity with modern data tooling such as dbt, Airflow, or equivalent orchestration/transformation frameworksExperience working with cloud infrastructure environments (AWS preferred)Strong understanding of ETL/ELT patterns, APIs, and scalable data workflowsHigh attention to data quality, reliability, and operational excellenceStrong communication skills and ability to work across technical and non-technical teamsBachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative disciplineNice to HaveExperience supporting AI/ML systems or datasets used in model developmentFamiliarity with embeddings, retrieval pipelines, or vector-based systemsExposure to AI-native development workflows and engineering productivity toolsExperience building dashboards, monitoring systems, or analytical applicationsPrior experience in financial services or highly analytical business environmentsWhy JoinWork on high-impact data and AI initiatives that directly influence strategic decisionsStrong ownership from day one in a technically challenging environmentExposure to a unique mix of engineering, analytics, and applied AICollaborate with highly analytical stakeholders on meaningful business problemsClear opportunity for growth, mentorship, and expanded technical responsibility

Created: 2026-05-14