Top Data & Analytics Jobs

Design and maintain scalable data solutions by developing advanced SQL queries, ETL pipelines, and SAP integrations. Build data models and data warehouse structures, support BI tools (Power BI), ensure data quality and governance, and partner with stakeholders to deliver analytics and documentation.

The Systems Integration Consultant will configure IBM TRIRIGA applications, analyze business requirements, assist in design and testing, and collaborate with teams.

Transform and validate large healthcare claims and eligibility datasets, perform data quality audits and reconciliation, design data mappings and ETL validations, generate recurring and ad-hoc reports, partner with engineers, data scientists, and business stakeholders to support analytics, ML use cases, and client deliverables, and drive continuous improvement in data architecture and reporting processes.

Lead and sustain enterprise master data operations (Material, Customer, Vendor, Pricing), enforce governance and SOX controls, drive data quality via KPIs and continuous improvement, support MDM/ERP initiatives, manage third-party providers, and develop data dictionaries, metrics, and process documentation.

Design and build production-grade data pipelines on Databricks and AWS extracting from enterprise ERPs, implement medallion architectures, ensure data quality/governance, collaborate with business SMEs, and deliver AI-ready data products.

The Director oversees data platforms and AI solutions, ensuring performance, reliability, and compliance while driving continuous improvement and data-driven decision making.

Support design, integration, validation, and reporting of HR data across systems (Workday, Snowflake). Define data elements and mappings, validate data quality, prepare reporting outputs, and collaborate with HR, Technology, Data, and client stakeholders to meet reporting requirements.

The Software Engineer will manage data collection for AI model training, enhance the ingestion pipeline on GCP, and collaborate with the AI team to improve dataset quality and efficiency.

Gather stakeholder reporting requirements, write clear report specifications, coordinate with BI to build and validate reports, analyze data accuracy, support stakeholders, and improve reporting processes.

Define and build core BI views and benchmarks for home-service verticals by working directly with customers. Translate messy operational CRM data into reusable, scalable insights and reports that improve customer performance. Partner with Product and Engineering to deliver production BI and drive company and customer outcomes.