Top Data & Analytics Jobs

Support affordable housing and land use consulting projects through GIS, spatial analysis, parcel prioritization, mapping, market studies, and quantitative and qualitative research. Analyze Census, PUMS, CoStar, and other datasets using ArcGIS, R, or Python; create publication-quality maps and graphics; provide technical assistance to local governments and community partners; collaborate with spatial analysts; review work products; and support project delivery, quality control, and client relationships.

Develops scalable data models, dashboards, reports, and analytical solutions that support business decisions. Partners with stakeholders to translate requirements, ensures data accuracy and usability, provides technical guidance to end users, documents architectures and processes, and communicates findings to technical and non-technical audiences. The role requires advanced Spotfire, SQL, and business intelligence experience, plus familiarity with modern data platforms and AI-assisted development tools.

Develop and maintain Power BI dashboards, reports, scorecards, data models, and analytical solutions for healthcare revenue cycle operations. Gather requirements, write and optimize SQL, validate data, resolve discrepancies, and deliver actionable financial and operational insights. Collaborate with leadership, technical teams, internal stakeholders, and clients while managing reporting projects, UAT, enhancements, automation, benchmarking, reimbursement analysis, and trend analysis.

Own Doctronic’s end-to-end data platform, including CDC pipelines from production databases into S3, Iceberg, and Snowflake; dbt transformations; orchestration; warehouse architecture; monitoring; and governed access to PHI. Establish trusted, documented data layers for analytics, finance, dashboards, and AI model training. Implement HIPAA-compliant access controls, anonymization, and deletion workflows while partnering autonomously with product, finance, marketing, partnerships, and AI teams.

Leads data engineering, cloud architecture, scientific software, and AI-enabled research platforms. Builds LLM, RAG, knowledge-search, and agentic workflows; integrates scientific systems; develops bioinformatics, genomics, clinical, and machine-learning data pipelines; and strengthens data quality, governance, lineage, security, observability, and reliability. Provides technical leadership across architecture, roadmaps, engineering practices, mentoring, and cross-functional collaboration.

Serve as an analytics subject matter expert guiding internal and external clients through business strategy discussions. Conduct discovery meetings, identify data analytics opportunities, design analytic solutions and proposals, communicate solution designs, and implement Decision Sciences products and services. The role requires expertise in data analysis, statistical modeling, consulting, business insights, and client presentations.

Mid-level analyst owning analytical projects end-to-end: build dashboards, reports, and data models; conduct structured analyses to surface insights; partner with Finance stakeholders; improve processes and automation; mentor junior analysts; and ensure data quality, documentation, and clear communication of findings to technical and non-technical audiences.

Design, build, maintain, and optimize Spark and Scala ETL/ELT pipelines on AWS for terabyte- and petabyte-scale datasets. Work across S3, Snowflake, Kafka, and monitoring systems, resolve production data-quality and performance issues, write automated tests, participate in architecture and code reviews, and support on-call operations. Use generative AI to improve pipeline development, monitoring, and engineering productivity.

Designs, develops, tests, deploys, and supports batch and streaming data pipelines using Azure and Databricks. Builds ETL/ELT processes, optimizes data workflows, supports cloud modernization, and performs monitoring, troubleshooting, and root cause analysis. Collaborates with business and technical teams on requirements, data governance, lineage, and audits. Mentors junior engineers and communicates solutions to technical and non-technical stakeholders.

Support enterprise data governance by curating metadata, managing business glossary terms, performing advanced data profiling/analysis, identifying anomalies, documenting issues, maintaining governance artifacts, and facilitating workshops to improve data quality and literacy.