Top Data & Analytics Jobs

Design, develop, and maintain scalable data pipelines, streaming applications, AI-powered solutions, and data platforms using Python, Spark, Scala, Kafka, and cloud technologies. Apply data warehousing, modeling, database design, performance tuning, security, and automation best practices. Support Azure Data Factory, Databricks, platform upgrades, vulnerability remediation, and operational stability while collaborating with cross-functional teams.

Lead the architecture, design, and implementation of scalable data pipelines and enterprise data assets supporting healthcare rebate and Medicaid systems. Ensure data quality, governance, security, and CMS compliance while troubleshooting complex integration and performance issues. Collaborate with engineering, analytics, business, and leadership teams to translate requirements into technical solutions. Use cloud, big data, and approved AI technologies to improve productivity, mentor teams, and support evolving healthcare and financial applications.

Analyze and manipulate claims data to support payment integrity and medical cost savings initiatives. Collaborate with claims analysts, ideators, and cross-functional data teams to identify savings opportunities, research data, troubleshoot anomalies, and ensure analytical accuracy. The role requires claims analysis experience, SQL and advanced Excel skills, and strong analytical capabilities. Python, data engineering, Snowsight, and claims platforms are preferred.

Leads the architecture and implementation of scalable data platforms, pipelines, ETL/ELT workflows, and cloud-native AWS data systems. Builds and optimizes Python, SQL, and Airflow pipelines; manages data warehouses, modeling, governance, quality, lineage, and security. Provides technical leadership and mentorship while collaborating with analytics, product, engineering, and business teams. Develops reliable, cost-efficient, highly available data infrastructure and translates business needs into scalable technical solutions.

Lead the design, development, optimization, and governance of enterprise-scale data pipelines, warehouses, lakes, and streaming systems. Build cloud solutions using Databricks and Azure, improve data quality and performance, implement CI/CD automation, support migrations, and enable analytics, reporting, and AI/ML initiatives. Collaborate with cross-functional stakeholders to translate requirements into scalable, reliable data platforms while meeting security, compliance, and SLA standards.

Develops and maintains automated Business Intelligence and reporting products, gathers stakeholder requirements, designs data solutions, mentors analysts, creates documentation, trains users, and collaborates with data strategy and IT teams. The role supports self-service reporting, data infrastructure improvements, product enhancements, and accurate delivery of reporting solutions for client account and sales teams.

Manage enterprise Power BI reporting environments, including workspace administration, security, governance, dashboards, and performance optimization. Develop advanced SQL and Snowflake solutions, validate data, troubleshoot reporting issues, and support end-to-end BI delivery. Collaborate with stakeholders, automate processes, maintain GitHub version control, mentor team members, and provide business intelligence expertise across executive, operational, product, and KPI reporting.

Design, build, and maintain scalable Azure data engineering solutions (Databricks, ADF, Snowflake). Develop ETL/ELT pipelines, batch and near real-time workflows, CI/CD and orchestration, and ensure data quality, security, and compliance in healthcare. Support production/on-call, collaborate with stakeholders on architecture, and apply GenAI techniques (RAG, LangChain). Contribute to API development (FastAPI) and containerized delivery (Docker).

Analyze healthcare ontology structures, search behavior, and administrative data to improve search relevance, data integrity, and configuration accuracy. Develop repeatable analyses and quality checks, support ontology and search enhancements, and translate complex datasets into actionable insights. Partner with Product, Technology, Operations, and Benefit Design stakeholders while documenting analytical methods and maintaining data standards.

Leads enterprise data engineering, architecture, modernization, and cloud transformation initiatives. Designs Azure-based Lakehouse, warehouse, ETL/ELT, governance, and AI-ready data platforms; mentors engineers; establishes DevOps, CI/CD, observability, security, and reliability practices; and supports critical production systems. Partners with stakeholders to deliver scalable data solutions for analytics, AI/ML, GenAI, and operational workloads, with a focus on healthcare data and enterprise architecture.