Top Data & Analytics Jobs

Supports production planning and digital transformation by analyzing manufacturing, inventory, scheduling, and production-performance data. Builds dashboards, reports, and visualizations; documents workflows; identifies automation and AI opportunities; assists with analytics and digital-tool pilots; validates data; researches emerging technologies; and presents recommendations to operations, planning, and leadership stakeholders in a manufacturing environment.

Build and maintain production-grade data models while migrating workflows from Alteryx to dbt. Manage Dagster or Airflow pipelines in Redshift, create Tableau dashboards, and translate technical data into RevOps insights. Partner with Sales, Marketing, and Customer Experience leaders on KPI reporting, ABM, and customer health scoring. Explore AI, LLM, predictive analytics, and SageMaker machine learning applications including churn prediction and lead scoring.

Lead the architecture and evolution of enterprise-scale data platforms, applying distributed-systems and advanced data-modeling patterns. Establish technical standards across dbt, Airflow, Snowflake, Kafka, ETL, cloud infrastructure, security, monitoring, CI/CD, testing, and source control. Solve complex data problems, partner with senior leaders, provide technical governance, mentor engineers, and drive platform and process improvements.

Designs and optimizes scalable data platforms, architectures, and production pipelines supporting AI and machine learning. Responsibilities include Databricks Lakehouse development, batch and real-time processing, data governance, security, monitoring, performance tuning, infrastructure planning, and collaboration with DevOps, MLOps, and cross-functional teams. The role serves as the AI team’s data engineering subject matter expert and ensures reliable, secure, cost-effective data solutions.

Owns the data and systems layer connecting Account Management and Carrier Procurement. Builds repeatable data pulls, pipelines, dashboards, automation, and trusted reporting across MercuryGate, DAT, Excel, and BI tools. Improves carrier tendering and pricing workflows, consolidates TMS and market data, supports development of a truckload rating engine, and partners with business leaders to deliver accurate, self-service data solutions.

Designs, builds, and operates governed AWS data lake infrastructure, self-service platform tooling, ETL/ELT pipelines, and data governance capabilities. Develops Python services supporting GenAI, RAG, and knowledge-based applications; contributes to streaming pipelines and large-scale PySpark processing. The role also manages infrastructure as code, observability, data quality, cost optimization, and platform reliability while partnering with engineering, data science, and business teams.

Leads advanced econometric, microsimulation, forecasting, causal inference, and policy-impact modeling for NYC policies and investments. Develops reproducible R-based analytical workflows, validates models, analyzes complex datasets, and communicates findings to technical and nontechnical stakeholders. Oversees complex research projects, mentors staff, collaborates with agencies and external partners, and translates quantitative results into policy recommendations.

Build and improve analytical tools and AI-enabled automations for Strategic Finance and cross-functional teams. Analyze data using SQL, BigQuery, Hex, spreadsheets, and AI tools; prototype, test, validate, document, and iterate solutions. Translate business problems into analytical requirements, collaborate with Data & Tech, evaluate AI-generated outputs, and help transition successful prototypes into tools used across Planning, Merchandising, E-commerce, Operations, and Growth.

Build and support production-grade Microsoft Fabric data products and pipelines across ingestion, transformation, lakehouse, warehouse, and curated layers. Implement reliable, restartable, and observable data solutions using medallion architecture, automated testing, governance, lineage, monitoring, CI/CD, and DataOps practices. Collaborate with architects, analytics, governance, application, and partner teams while documenting mappings, runbooks, controls, and operational procedures.

Conduct quality audits across support, sales, renewals, and underwriting teams; evaluate compliance and customer interactions; validate AI-generated quality assessments; refine scorecards and calibration processes; identify trends, risks, and process gaps; and recommend corrective actions. The role also supports testing Talkdesk and other quality technologies, documenting evaluation criteria, and determining where automation or human review is appropriate.