Top Analytics Engineer Jobs in NYC, NY

Build and own the product analytics foundation: define core metrics, model data, create dashboards for funnels/retention/activation, analyze user journeys, respond to customer analyses, and partner with engineering on event instrumentation and data pipelines to ensure high data quality.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

As an Analytics Engineer, you will develop data pipelines, analytics frameworks, and dashboards to support data-driven decisions and enhance customer acquisition. Collaborate with various teams to transform business needs into scalable data solutions while ensuring data integrity and quality.

Design, build, and maintain dimensional models and data transformations in dbt to convert operational data into reliable analytical assets. Collaborate with subject-matter experts to capture business logic, implement automated tests and monitoring, contribute to the semantic layer, support the analytics platform, and execute small-to-medium projects under senior guidance.

Design, build, and maintain a centralized data warehouse and analytics platform. Create scalable data models, ETL/ELT pipelines, and semantic layers. Improve data quality, governance, lineage, and accessibility. Partner cross-functionally to define metrics, enable self-service analytics, and standardize data models across products and teams.

Build and maintain a cloud-native, high-SLA Alpha Platform for pre-trade analytics, risk, hedging, and portfolio optimization. Work across full stack from data ingestion and processing to AI-driven analytics and client APIs. Drive system design, own features end-to-end, mentor peers, and promote engineering standards, observability, and CI/CD best practices.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

The role focuses on implementing cost optimization solutions for cloud infrastructure through automation and collaboration across teams, enhancing FinOps practices.

Build and maintain data pipelines and dbt models, own reporting and dashboards across Finance, GTM, Product, and Engineering, support third-party financial data integrations, enable GTM and customer-facing analytics, and ensure data quality, testing, and documentation.

Lead definition and maintenance of business metrics and data models, build dashboards and reports, act as data subject-matter expert across sales/finance/operations, ensure KPI integrity, and enable analytics teams to deliver insights.

Build and maintain scalable data models and pipelines (especially Market Data) using dbt and Airflow; implement data observability, testing, and monitoring; collaborate with data scientists, product, and engineering to deliver production data products that drive revenue and customer value.

Fora seeks a Senior Analytics Engineer to enhance data modeling and delivery, ensuring access to reliable insights across teams. Responsibilities include managing the analytics layer, improving data performance, and mentoring while collaborating with stakeholders on analytics needs.

Build, maintain, and validate production data pipelines and ETL infrastructure (BigQuery/GCS/dbt/Airflow alternatives). Ensure data observability, SLAs, and automated tests to deliver reliable datasets that support campaign decision-making and organizers. Collaborate with product and data teams across fast-paced, cycle-driven work.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

The Analytics Engineer will design and implement analytics solutions, maintain reporting dashboards, partner with Product on KPIs, and support marketing with analytics.

The Data and Analytics Engineer will build and maintain scalable ELT pipelines, leveraging data for analytics and reporting within the Snowflake data architecture.

Develops business intelligence, reporting, data pipelines, dashboards, and geospatial solutions for complex real estate portfolios. Transforms and integrates data from multiple sources, builds scalable analytics products, automates reporting processes, and supports portfolio planning, occupancy strategy, workplace initiatives, and operational decision-making. Partners with stakeholders and clients to translate business needs into technical solutions, communicate insights, train users, and improve analytics adoption. The role also supports geospatial capabilities and leverages emerging AI-enabled tools.

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

As an Analytics Engineer, transform raw data into metrics, manage data pipelines, ensure data integrity, and collaborate with teams for analytics solutions.

Design and build end-to-end analytics pipelines and dimensional data models on Snowflake. Own data ingestion, transformations, testing, monitoring, and ad hoc analytics; partner with stakeholders to turn ambiguous business needs into reliable, consumable datasets.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Design, build, and maintain end-to-end data models and pipelines to support CX operations, compliance reporting, and customer insights. Create dashboards and metrics, enforce data quality and governance, automate recurring workflows, and partner with stakeholders and broader data teams to deliver self-serve analytics solutions.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Design, build, and maintain scalable ETL/ELT pipelines and analytics-ready data models using Python and SQL. Implement GitLab CI/CD, develop dashboards in Tableau/Power BI, perform data cleaning and analysis, support modeling and AI initiatives, document metadata, and mentor junior staff while collaborating with cross-functional teams to deliver actionable insights.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.