Top Data & Analytics Jobs

Design and maintain a centralized SQL Server database, data model, and Python/SQL ETL pipelines integrating business systems such as NetSuite, Arena, ION, and Jira. Build Power BI dashboards and KPI reports, support NetSuite customizations, and partner with cross-functional teams to deliver integrations and technical solutions. The role also promotes data quality, governance, documentation, and change control.

Coordinates data management, quality improvement, performance measurement, and program evaluation for the Prevention and Advocacy Division. Collects, analyzes, and reports program data; maintains accurate databases; develops dashboards and reports; supports audits and regulatory reporting; monitors data quality; and identifies process improvements. Collaborates with leadership, internal teams, external stakeholders, committees, and workgroups to improve program outcomes and ensure compliance with data security and reporting standards.

Provides database and marketing analytics support for casino player-tracking systems. Responsibilities include building offers, maintaining data quality, preparing direct-mail and digital marketing lists, creating reports and ad-hoc analyses, writing SQL queries and scripts, automating data exports, supporting ETL, maintaining audit logs, and providing data-driven recommendations for player retention and acquisition. The role is fully on-site and may require nights, weekends, and holidays.

Build and maintain Snowflake data infrastructure using dbt, including scalable data models, dimensional models, data marts, and ELT/ETL pipelines. Implement data quality, governance, lineage, documentation, and performance optimization practices. Collaborate with analysts and business stakeholders to translate requirements into reliable analytics solutions while applying software engineering practices such as testing, version control, peer review, and CI/CD.

Build and optimize real-time and batch data pipelines, integrations, data warehouses, ETL processes, and reconciliation systems. Develop complex SQL queries, APIs, analytic reports, and data tools while supporting production pipelines and troubleshooting data integrity issues. Partner with architects, analysts, developers, and cross-functional teams to improve data reliability, quality, scalability, and accessibility across cloud and on-premises environments.

Supports Business Compliance projects through data extraction, analysis, validation, reconciliation, reporting, and process documentation. The intern will work with SAP data and analytics platforms including Power Query, Alteryx, and Databricks Genie Rooms, validating dashboards and reporting against source data. The role provides experience in business intelligence, data visualization, generative AI prompting, and data-driven decision-making while collaborating with compliance teams and documenting procedures and reporting logic.

Lead master and reference data strategy, governance, operating models, and platform modernization for Everest’s global insurance business. Define requirements, target architecture, ownership, stewardship, controls, workflows, data quality standards, lineage, reconciliation, and regulatory practices. Partner with business and technology stakeholders to implement trusted records, hierarchies, taxonomies, automation, and governed self-service. Oversee operations, issue management, reporting, adoption, and continuous improvement across enterprise data platforms and products.

Lead Databricks engineering efforts for enterprise-scale data and analytics platforms in hybrid cloud environments. Design, develop, integrate, and maintain data solutions; resolve technical issues; guide architecture and engineering teams; ensure data quality and observability; coordinate client installations; manage expectations; contribute to product roadmaps; and support deployment, maintenance, modernization, and troubleshooting at customer and Navy sites.

Principal technical leader responsible for architecting and operating relational data marts, dbt data products, semantic layers, and shared data services. Builds scalable solutions in Databricks, Delta Lake, and Spark; owns data products through testing, deployment, documentation, monitoring, and support. Establishes governed metrics, data quality, lineage, observability, and access controls while partnering cross-functionally to resolve ambiguity. Mentors engineers, improves reusable frameworks, and supports BI, data science, and AI use cases.

Lead the architecture and development of scalable data pipelines and infrastructure. Clean, standardize, and model construction data; build tools for data quality and performance; design integration flows with product, engineering, and customers; apply Python, SQL, and ETL practices; and use AI/ML to improve data classification and mapping. Establish data governance and reliability standards in a high-ownership startup environment.