Top Data & Analytics Jobs

Design, build, and maintain scalable ETL/ELT pipelines and data integrations to consolidate, transform, and prepare large datasets for analytics and ML. Enforce best practices, data governance, monitoring, and support while collaborating with business and analytics teams to improve data quality and enable insight-driven decisions.

Develops Power BI and Tableau dashboards, automated reports, and analytics solutions. Performs ETL across multiple data sources, supports data warehousing and architecture initiatives, analyzes business requirements, and ensures data quality and compliance. Collaborates with stakeholders to identify trends and improve processes, with a focus on healthcare reporting, large datasets, and data-driven decision-making.

Develop and maintain enterprise Power BI dashboards, semantic models, and reporting solutions. Integrate Azure and Databricks data, write Python and PySpark transformations, optimize DAX and data models, implement security, and ensure data quality. Collaborate with stakeholders, engineers, and architects to translate requirements into scalable solutions. Lead technical teams, conduct architecture reviews, manage Fabric platforms, and train business users on Power BI.

Leads technical delivery of Master Data Management solutions using Informatica MDM and PowerCenter. Designs and implements ETL mappings, workflows, transformations, data quality processes, governance practices, SQL data marts, and Python automation. Oversees MDM specialists, monitors production jobs, troubleshoots operational issues, supports testing and validation, tunes performance, documents technical solutions, and collaborates with state agencies, QA, business teams, and project leadership.

Design, build, test, and maintain scalable data engineering solutions, including automated releases, ETL processes, data models, real-time pipelines, monitoring, legacy migrations, and security strategies. Transform raw data using business logic, support machine learning and business intelligence workloads, and produce technical documentation. The role requires extensive experience with cloud platforms, SQL, databases, data warehousing, Spark, Databricks, Airflow, Kubernetes, Docker, Python, and related data technologies.

Design and maintain scalable Databricks data pipelines, orchestrate workflows with Airflow, and build optimized Snowflake ELT solutions. Develop Python-based APIs and data services deployed on Azure, applying cloud security, scalability, monitoring, and cost-optimization practices. Implement data quality and observability controls, collaborate with analytics and platform teams, participate in architecture and code reviews, and resolve complex production issues across data infrastructure.

Build and maintain scalable ETL pipelines, integrate data from databases, APIs, streaming platforms, and external providers, and transform large datasets for analytics and machine learning. Establish reusable engineering frameworks, data governance, monitoring, alerting, and reliability practices. Collaborate with analytics and business teams on cloud data migration, predictive model enablement, and healthcare cost reduction. Required skills include SQL, Python, Scala or Java, cloud platforms, Snowflake or Databricks, DevOps, Git, and CI/CD.

Analyze healthcare risk adjustment and health plan data across Medicare, Medicaid, and ACA Commercial programs. Build and maintain reliable data solutions using SQL, Python, ETL processes, databases, Tableau, Power BI, and Excel. Investigate application, data, system, and workflow issues, identify root causes, recommend corrective actions, and collaborate with technical teams to resolve problems.

Provide technical leadership for analytics engineering across enterprise platforms. Design and optimize scalable Databricks data pipelines using Python, PySpark, and SQL; develop governed Power BI solutions, semantic models, dashboards, and executive reporting. Partner with stakeholders to define metrics, deliver AI-enabled insights, and improve decision-making. Ensure data quality, lineage, security, and governance while optimizing models, queries, and pipelines. Lead large-scale technical initiatives, influence architecture, and guide analytics engineers.

Lead enterprise data strategy, governance, platforms, and operating model to enable reliable, secure, and AI-ready data. Establish standards, stewardship, and shared capabilities across a federated organization, drive adoption and measurable business impact, partner with executives and compliance, and build a multidisciplinary data organization.