Top Senior Data & Analytics Jobs

Analyze AI Search data to identify meaningful questions, build recurring reporting, investigate changes in visibility and model behavior, refine measurement methods, and translate findings into product, customer, and prospect recommendations. Partner with Product and Data teams, create customer-ready analyses and presentations, communicate findings to varied audiences, and document methods and limitations. The role requires strong SQL skills, analytical judgment, and the ability to work with complex datasets.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Manage complex SQL Server and Azure SQL environments, including database architecture, data modeling, ETL, stored procedures, reporting, performance tuning, security, backups, recovery, patching, failover, and production support. Develop SSIS and Azure Data Factory pipelines, optimize queries and indexes, administer permissions and encryption, maintain SSRS and Power BI reporting, document technical solutions, and supervise staff or projects.

Provide workforce analytics and consulting support to HR leaders across Services and Sales Operations. Develop reporting, staffing, retention, and productivity insights; solve complex business problems with quantitative and qualitative data; create executive-ready narratives; influence analytics and product roadmaps; and advise senior leaders on workforce measures and actionable solutions.

Gather and document business requirements, translate business needs into technical specifications, and liaise between stakeholders and technology teams. Develop and execute test plans, integration tests, regression tests, and support UAT. Validate solutions against requirements, resolve issues with developers, assist with release planning and post-deployment validation, and maintain project and testing documentation across concurrent technology initiatives.

Lead the firm’s analytics strategy, roadmap, and growing analyst team. Partner with executives and law firm operations leaders to define KPIs, evaluate performance, identify bottlenecks, build forecasting and predictive capabilities, and translate data into business actions. Guide SQL, Python/R, statistical modeling, visualization, data quality, and analytics infrastructure standards while partnering with technology and data engineering teams to embed insights into operational workflows.

Manage client relationships and deliver consumer, market, and industry insights using NIQ data and analytics tools. Translate complex data into clear stories, recommendations, and business actions; respond to client questions; identify revenue opportunities; execute service models; lead thought leadership projects; and coach junior team members. The hybrid role requires onsite work in Corona, California, at least three days weekly.

Leads marketing analytics capabilities, including KPI frameworks, recurring reports, executive dashboards, forecasting, predictive modeling, segmentation, and data governance. Translates marketing and business data into recommendations on acquisition, retention, channel performance, ROI, LTV/CAC, and brand health. Directs analytics resources and partners with Marketing, Sales, Finance, and leadership to support data-driven planning, reporting, and strategic decision-making.

Builds and maintains production-grade ETL/ELT pipelines across legacy on-premise systems and AWS/Azure cloud platforms, centralizing data in Snowflake for analytics, machine learning, feature stores, and generative AI. Develops vectorization and embedding pipelines, optimizes Snowflake performance and cloud costs, manages cross-platform orchestration, and implements data quality and observability frameworks. Partners with IT, security, MLOps, data science, and infrastructure teams to deliver scalable, governed data solutions.

Leads a team delivering enterprise data products using Snowflake, dbt, SQL, and Azure. Designs transformation and dimensional modeling layers, establishes engineering and quality standards, embeds testing into CI/CD, optimizes Snowflake performance and costs, and applies governed AI-assisted development. Manages delivery priorities, partners across data and business teams, hires and develops employees, and ensures auditability, governance, and SOX compliance in a regulated banking environment.