Associate Analytics Engineer: Data Pipelines & Dashboards

ICONIQ; New York (NY); Hybrid; USD 150,000 - 170,000; Full time

Job summary

ICONIQ is seeking an Associate, Analytics Engineer to join the Data & Analytics team in New York. You will translate business questions into analytical insights and scalable data solutions, spanning metrics, modeling, pipelines, integrations, and dashboards.

The ideal candidate will be analytically rigorous, commercially minded, and capable of moving between business conversations, analysis, and data engineering.

Qualifications

• 4+ years of relevant experience in analytics engineering, data analytics, data engineering, business intelligence, or a related discipline.
• Strong analytical and commercial orientation with ability to structure ambiguous business questions.
• Ability to translate findings into actionable insights and scalable data products.
• Experience building scalable data models, transformation pipelines, and production-quality workflows.

Responsibilities

• Partner with Corporate Finance, People Ops, Operations, Technology, and other stakeholders to translate priorities into analytical solutions.
• Develop analytical models and data products across financial, workforce, operational and enterprise data.
• Design and maintain KPI frameworks, executive reporting, dashboards, and self-service analytics.
• Build scalable data models, transformations, and workflows using SQL, Python, and APIs.
• Establish data quality, governance, and observability to improve accuracy and transparency.
• Collaborate to evolve the cloud data platform and explore AI-enabled analytics.

Skills

SQL

Python

Data modeling

Analytics eng

Dashboards

Stakeholder collab

Data quality

Cloud platforms

Testing

Tools

Snowflake

Databricks

BigQuery

Redshift

Tableau

Power BI

APIs

Job description

ICONIQ is seeking an Associate, Analytics Engineer to join the Data & Analytics team in New York. You will translate business questions into analytical insights and scalable data solutions, spanning metrics, modeling, pipelines, integrations, and dashboards.

The ideal candidate will be analytically rigorous, commercially minded, and capable of moving between business conversations, analysis, and data engineering.