Top Data & Analytics Jobs

Analyze complex data to support business decisions across marketing, finance, product, sales, medical affairs, and customer success. Responsibilities include defining data requirements, developing and automating data pipelines, building interactive dashboards, identifying trends and process improvements, and presenting insights to executives and external partners. The role requires advanced SQL, Python, BI, visualization, and cross-functional analytics experience, with an emphasis on using AI to improve efficiency.

Leads analytics for B2B sales, partnerships, revenue operations, and marketing teams. Responsibilities include forecasting, opportunity sizing, partner performance analysis, enterprise market intelligence, RFP analytics, lead scoring, funnel and lifecycle optimization, predictive modeling, experimentation, and executive insight generation. The role partners with Data Science and Engineering teams to improve revenue growth, onboarding, retention, campaign effectiveness, and sales performance across enterprise and SMB channels.

Designs and develops large-scale streaming data systems, scalable infrastructure, data pipelines, and data models for Coupang’s seller marketplace. Owns projects from architecture through delivery, improves platform scalability and reliability, contributes to shared engineering standards, and provides technical leadership across teams. The role requires backend software expertise, distributed systems experience, and proficiency with Java, Spring, AWS, and data technologies such as Spark, Flink, Kafka, and NoSQL.

Designs and maintains enterprise healthcare EDI data pipelines for HIPAA X12 transactions, Medicaid encounters, and CMS compliance. Builds ETL/ELT workflows using Databricks, PySpark, Delta Lake, and SQL Server; develops validation, reconciliation, monitoring, and alerting frameworks; troubleshoots clearinghouse integrations; supports regulatory updates and encounter submissions; and collaborates with claims, compliance, security, product, and external healthcare teams.

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.