Top Senior Data & Analytics Jobs

Conduct market, competitive, customer, product, industry, and performance analysis to support data-driven decisions across Lifecycle Services. Develop market insights and plans, guide go-to-market activities, monitor competitors, build cross-functional data-sharing programs, and support voice-of-customer, partner, and employee research. Collaborate with product management, marketing, sales, and global teams while using AI-based tools and quantitative and qualitative research methods.

Provides technical and architectural leadership for enterprise data engineering, ETL modernization, and cloud migration across Azure and AWS. Designs data models, ingestion frameworks, ADF and AWS Glue pipelines, CRM integrations, MDM solutions, and retention processes. Leads migration from SQL Server and SSIS to cloud platforms, modernizes VB6 systems with C#, optimizes databases, ensures security and compliance, and mentors engineers. Collaborates across cloud, CRM, infrastructure, security, and product teams to deliver data platform modernization milestones.

Analyze complex healthcare and business data from enterprise data warehouses and source systems. Build data models, dashboards, reports, and predictive analyses using Power BI and other tools. Partner with clinical, operational, financial, accounting, IT, and BI leaders to define KPIs, improve reporting, maintain data integrity, and translate findings into actionable recommendations. Support governance and HIPAA compliance across a multi-site dental organization.

Lead data management across batch and streaming environments; design and maintain ETL pipelines; develop Databricks and Apache Spark solutions; manage real-time processing, data transformation, routing, and enrichment; optimize storage and retrieval performance; support data security and compliance; and document processes. The role requires expert Databricks knowledge and technical leadership while collaborating with security, data science, and AI engineering teams.

Provides data-driven insights for business stakeholders by extracting, transforming, analyzing, and visualizing data. Develops dashboards and reports, integrates disparate data sources, supports data governance and quality initiatives, coordinates analytics and IT requirements, assists with data science modeling, and translates complex analysis into actionable recommendations. The role also trains staff on data definitions, sources, coding structures, and analytics tools.

The role involves leading AML reporting efforts, improving data governance, ensuring data quality, and managing a team of analysts to deliver insights through dashboards and reporting.

Document and reverse-engineer the client's ServiceNow data model and ITSM/CMDB processes. Design API-based incremental extraction into a Bronze layer and specify Bronze->Silver->Gold mappings. Define DNA crosswalk keys, data-quality gates and KPI confidence scoring, and support pipeline development, observability, and automated testing for ServiceNow as a source system.

Administer and implement enterprise database platforms across Google Cloud and other cloud environments. Manage SQL Server, BigQuery, Cloud SQL, security, backups, monitoring, performance tuning, query optimization, schema design, data pipelines, cost optimization, and governance. Provide technical support, troubleshoot incidents, manage releases and database-as-code, respond to on-call issues, and collaborate with IT and application teams. Improve operations through automation and AI tools while documenting solutions and supporting users.

Designs and implements enterprise database architecture, relational databases, data warehouses, data models, archiving strategies, and migration solutions. Develops database security, backup, and recovery specifications; provides MIS and database operational support; codes utilities; resolves user issues; and supports legacy-system migrations. The role also requires collaboration, technical training, and expertise in Oracle, ETL, PL/SQL, and dimensional data modeling.

Owns the strategy, roadmap, and delivery of marketing data products supporting customer insights, campaign execution, measurement, personalization, and analytics. Partners with marketing, analytics, engineering, technology, and governance teams to translate business needs into scalable data solutions. Responsibilities include data modeling, pipelines, dashboards, semantic layers, data quality, governance, KPI standardization, stakeholder management, backlog prioritization, and enablement of segmentation, attribution, and AI/ML initiatives.