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Associate, Analytics Engineer

ICONIQ Capital LogoICONIQ Capital
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Salary

$150,000 - $170,000

Location

New York, NY

Posted

Today

The Associate, Analytics Engineer will join ICONIQ’s Data & Analytics team within Technology, partnering across corporate functions to drive data-informed decision-making. The role combines analytical and commercial thinking with the technical skills to translate business questions into actionable insights and scalable data solutions.

The Associate will work across the analytics lifecycle, from defining metrics and analyzing performance to building data models, pipelines, integrations, and dashboards. The ideal candidate is curious, commercially minded, analytically rigorous, and technically capable, with the ability to move between business conversations, analysis, and data engineering.

What you'll do

  • Partner with Corporate Finance, People Operations, Operations, Technology, and other stakeholders to understand business priorities, translate complex questions into analytical solutions, and proactively identify opportunities where data can improve decision-making and business outcomes.
  • Conduct structured analyses and develop analytical models and data products across financial, workforce, operational, and enterprise data, applying business context and sound judgment to identify trends, drivers, opportunities, and actionable insights.
  • Develop and maintain KPI frameworks, executive reporting, dashboards, and self-service analytics capabilities that provide trusted visibility into business performance and support financial planning, workforce planning, operational performance, and other corporate priorities.
  • Design, build, and maintain scalable data models, transformation pipelines, integrations, and workflows, leveraging SQL, Python, APIs, and modern data engineering practices to create reliable foundations for analytics and reporting.
  • Establish trusted and consistent enterprise data by partnering on business definitions and metrics and implementing data quality, monitoring, governance, documentation, and observability practices that improve accuracy, accessibility, and transparency.
  • Advance ICONIQ’s analytics and data capabilities by collaborating across Analytics and Technology teams to evolve the cloud data platform and evaluate emerging data and AI technologies that can improve analytics, automation, engineering efficiency, and stakeholder outcomes.

Qualifications

  • 4+ years of relevant experience in analytics engineering, data analytics, data engineering, business intelligence, or a related discipline, ideally supporting corporate or enterprise functions such as Finance, FP&A, Accounting, Operations, or People Analytics.
  • Strong analytical and commercial orientation, with demonstrated ability to structure ambiguous business questions, analyze complex datasets, identify meaningful trends and drivers, and translate findings into actionable insights.
  • Strong proficiency in SQL and working proficiency in Python, with experience building and maintaining scalable data models, transformation pipelines, analytical products, and production-quality workflows with appropriate testing, monitoring, and data quality controls.
  • Strong understanding of modern data architecture and engineering practices, including data warehousing, dimensional modeling, ETL/ELT, workflow orchestration, APIs and system integrations, and cloud data platforms such as Snowflake, Databricks, BigQuery, or Amazon Redshift.
  • Experience partnering directly with business stakeholders to define requirements, metrics, and analytical solutions, including developing dashboards, executive reporting, KPI frameworks, and self-service analytics using Tableau, Hex, Sigma, Power BI, or similar platforms.
  • Excellent communication, collaboration, and execution skills, with the ability to independently manage multiple priorities in a fast-paced environment, exercise sound judgment when working with sensitive enterprise data, and demonstrate curiosity about emerging technologies, including AI and AI-enabled analytics.

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