Top Analytics Engineer Jobs in NYC, NY

Build and maintain dbt models and daily pipelines, monitor and triage ETL runs, develop Omni BI views, collaborate cross-functionally, and document data assets to enable data-driven decisions.

Build Sailor Health’s foundational data platform from scratch. Responsibilities include developing Snowflake and dbt pipelines integrating EHR, CRM, and communications data; creating data-powered web applications; automating clinical and billing workflows with Python; analyzing therapy transcripts and patient data using AI and machine learning; tracking clinical outcomes; and designing scalable data architectures in collaboration with clinicians, engineers, founders, and other teams.

Design and build scalable data pipelines, models, and dashboards for supply chain KPIs. Partner with business stakeholders to enable forecasting, scenario planning, data governance, automation, and actionable reporting for leadership and projects.

Build and own the data warehouse, analytics, and self-serve BI; define metrics and data models; prepare datasets for ML/AI features; partner cross-functionally to deliver dashboards, ensure data quality, and document systems as the companys first analytics hire.

The Staff Analytics Engineer leads the design and implementation of data solutions, enhancing analytics capabilities across Zocdoc, collaborating with multiple teams to drive strategic insights.

Build and maintain governed Silver/Gold data models and semantic assets on Databricks. Translate stakeholder KPIs into testable, reusable transformations, apply enterprise modeling standards, enable domain self-service, ensure data sensitivity and governance, and review domain-contributed models for production readiness.

Build, refactor, and operate a production RWD delivery pipeline using dbt, PySpark, Snowflake, and AWS. Own delivery endpoint configs as code, enforce HIPAA de-identification, manage monthly deliveries, drive data quality metrics and investigations, support channel partners, and collaborate with platform engineering using CI/CD, Argo orchestration, and observability tools.

Lead design and delivery of scalable analytics engineering solutions: build dbt transformation pipelines on Databricks/Postgres/BigQuery, develop tested dimensional models and feature tables, implement data quality and governance, improve SDLC and CI/CD, create reusable dbt patterns and semantic metrics, and engage stakeholders to translate requirements and mentor junior engineers.

Build scalable data solutions and reconciliations to automate Compliance & Finance regulatory processes. Partner with stakeholders to translate requirements into designs, lead technical development, review code, and evolve standards for data pipelines and reporting.

Design, build, and maintain data transformations and models using SQL and dbt to support enterprise reporting and AI initiatives. Implement data quality controls, create analytics datasets, and collaborate with engineering and business teams to deliver trusted dashboards, metrics, and information products.

Design, build, and maintain scalable dbt transformation pipelines and analytical data products on cloud platforms. Own data product lifecycle from source alignment and modeling to deployment, testing, monitoring, and governance. Implement automated data quality, observability, and metadata practices; develop reusable macros and semantic-layer assets. Collaborate with stakeholders, mentor peers, and promote analytics engineering standards to support reporting, advanced analytics, and AI use cases.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Build and operate a hyper-scale data lake and analytics platform: develop Java microservices and Spark/Scala/Flink pipelines, own a new graph database, design ultra-high-scale data platforms, optimize performance and latency, enable efficient querying for analytics and ML, and collaborate on feature design and stability across teams.

Design, implement, test, and deploy high-performance C++ APIs exposing a mortgage analytics quantitative library for interest rate modeling, prepayment/default analysis, derivative valuation, hedging, and forecasting. Improve performance, reliability, and usability of the library and collaborate with business, model development, validation, and IT teams.

Lead architecture, systems, and roadmap for Coinbase's Compliance Reporting Data Platform. Design and build production-grade data models, pipelines, quality frameworks, validations, and certification processes. Establish data contracts, monitoring, reconciliation, and audit-ready processes. Partner with engineering and compliance stakeholders, respond to regulatory exams, and mentor engineers while shaping standards and documentation.

Build and maintain analytics data systems and pipelines that capture, transform, and integrate product usage data at scale. Deliver accurate insights and visualizations to inform product decisions, collaborate cross-functionally, and apply AI tools to improve analytics and workflows.

Design and build data warehouse architecture, dimensional models, data marts, and transformation pipelines (dbt, Airflow, BigQuery). Partner with analysts, data scientists, and engineers to enable reporting in Looker, ensure data quality and reconciliation, and support cross-functional analytics needs across business teams.

Build and validate SQL transformations mapping healthcare financial and clinical data into a unified ontology and semantic layer. Reverse-engineer customer business rules, own testing and data correctness, manage historical backfills and incremental loads, and collaborate with customers and platform, insights, and product engineering teams. The role requires strong healthcare revenue-cycle data expertise, production Python, modern data-platform experience, transformation-as-code workflows, data modeling, and customer-facing requirements discovery.

The Founding Analytics Engineer will create and implement the analytics infrastructure, establish data models, define metrics, and enable data-driven decision making for healthcare practices.

The Senior Analytics Engineer will manage the analytics layer, owning dbt projects, orchestrating data pipelines, defining metrics, and ensuring data quality while mentoring the data team.

Build analytical models, pipelines, integrations, dashboards, KPI frameworks, and executive reporting across finance, workforce, operational, and enterprise data. Partner with stakeholders to translate business questions into actionable insights, establish trusted metrics, and implement data quality, governance, monitoring, and documentation practices. Contribute to cloud data platform improvements and evaluate emerging AI and analytics technologies.

Designs and develops scalable data pipelines, models, schemas, and analytics workflows. Builds tested, documented, version-controlled data solutions using ETL/ELT principles, orchestration, and modeling frameworks. Creates high-performance Tableau or Looker dashboards, ensures data integrity, and partners with engineering and business stakeholders to enable self-service analytics and data-driven decisions.

Build and maintain Clair’s ELT pipelines and dbt data models, ingest new source systems, and create trusted datasets for analytics and business decisions. Improve data quality, testing, documentation, observability, governance, and access controls. Partner with analysts, data scientists, engineers, and business stakeholders to define metrics and resolve data issues. Support feature pipelines, optimize Snowflake costs, and occasionally provide ad hoc analysis.

The Senior Analytics Engineer at Rockstar Games will develop data infrastructures, optimize data models, and collaborate with Data Scientists and Engineers to provide actionable insights.

Build and maintain Salesforce reports and Sigma dashboards, manage CRM data hygiene and Data Cloud integrations from the Databricks data lake, handle ad-hoc commercial reporting, and support AI initiatives tied to sales and commercial strategy.