Top Senior Data & Analytics Jobs

Designs and maintains scalable analytics data models, pipelines, warehouses, governance processes, data quality checks, and reporting infrastructure. Partners with engineering, product, and business stakeholders to define metrics, improve data integrity, develop dashboards, enable self-serve analytics, and train users on data tools. The role also supports PermitFlow’s data stack and uses LLMs to enhance analytics workflows.

Designs and maintains secure, scalable Microsoft Fabric data pipelines, Lakehouses, warehouses, and infrastructure. Implements encryption, access controls, governance, compliance, monitoring, CI/CD, infrastructure-as-code, containerization, and automated security testing. Collaborates with security, platform, data science, and engineering teams to improve data reliability and operational excellence. Requires strong SQL, data engineering, Azure, DevOps, and data security experience, along with US citizenship.

Analyzes constellation capacity, customer demand, product usage, revenue, pricing, and operational performance. Maintains and improves Python- and SQL-based workflows and business intelligence datasets, develops quantitative analyses for Product and Sales teams, and translates complex data into actionable recommendations for technical and non-technical stakeholders.

Lead enterprise data engineering efforts supporting defense missions. Responsibilities include prioritizing technical tasks, mentoring engineers, conducting code reviews, translating government requirements into scalable data architectures, developing Databricks ETL/ELT pipelines with Python, PySpark, and SQL, troubleshooting pipeline performance and reliability, and documenting systems. The role collaborates with government stakeholders, product owners, data scientists, analysts, and technical teams to deliver secure, high-throughput data platforms and actionable insights.

Build and maintain data products, dbt models, ELT pipelines, data warehouses, Looker explores, and visualizations. Drive analytics strategy, self-service BI, data governance, security, observability, lineage, and stewardship. Mentor engineers, apply software engineering practices, solve complex business problems, and collaborate cross-functionally. Lead AI-powered analytics improvements, including intelligent monitoring, automated data quality checks, responsible AI governance, and AI-assisted development.

Conduct advanced research and analysis of Medicaid and CHIP data using statistical methods, predictive modeling, data mining, and qualitative research. Develop analytic products, dashboards, reports, visualizations, and technical deliverables that support CMS policy, operations, oversight, and health outcomes. Collaborate with analysts, data scientists, clients, and technical teams in an agile environment while leading research projects and translating complex findings for diverse audiences.

Leads the data, analytics, and AI team; consolidates the company data warehouse; governs cross-system reporting and metric definitions; oversees pipelines, data quality, security, and upstream integrations; prioritizes the team backlog; manages and grows a distributed team; and delivers automation and AI tools. The role requires strong data engineering, analytics, BI, governance, business communication, and platform decision-making skills. Travel occurs approximately quarterly.

Leads marketing optimization analytics by framing ambiguous business questions, conducting deep-dive performance analyses, measuring media effectiveness, optimizing spend, and managing incrementality testing. Develops evidence-based recommendations for marketing leadership and Finance, partners with media, brand, agency, and data teams, and communicates complex findings to senior stakeholders. The role requires expertise in marketing mix modeling, experimentation, SQL, and marketing performance data.

Leads data analytics for Real Estate Finance by modernizing reporting infrastructure, building Power BI dashboards, developing forecasting and portfolio performance models, and delivering executive insights. The role supports cloud analytics platforms using GCP and BigQuery, strengthens data governance, enables self-service reporting, and explores AI/ML applications. It partners with Finance, IT, and business stakeholders to define KPIs, improve data quality, and translate financial and operational data into strategic recommendations.

Designs and maintains scalable Azure data pipelines and ETL/ELT solutions across data lakes, warehouses, lakehouses, streaming platforms, and enterprise sources. Builds integrations using Azure Data Factory, Synapse, Databricks, Spark, Kafka, and related services; applies security, governance, monitoring, and performance optimization practices. Develops Power BI dashboards, reports, data models, and visualizations, while supporting analytics and AI/ML use cases. Collaborates in Agile teams and automates deployments through DevOps and CI/CD practices.