Top Senior Data & Analytics Jobs

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Leads complex quantitative and qualitative analysis for Claims Leadership, producing forecasts, reports, dashboards, KPI frameworks, and actionable recommendations. Analyzes multiple data sources, identifies trends and root causes, supports strategic decisions, documents processes, and consults with cross-functional partners. Coaches peers on analytical methods and applies statistical research, visualization, and data storytelling techniques to improve business outcomes.

Lead the design and delivery of governed data products for Finance and GTM teams. Build datasets, semantic models, reporting and planning solutions, and AI-enabled analytics workflows on Databricks. Establish modeling, metric, architecture, and quality standards; manage reconciliation and acceptance; partner cross-functionally with data engineering; and mentor engineers and Finance stakeholders.

Develop and maintain Java applications, RESTful APIs, backend services, and cloud-ready integrations using AWS. Write optimized SQL, automate tasks with Bash, manage code with Git, troubleshoot production issues, and participate in architecture discussions, code reviews, and continuous improvement. The role requires ownership of end-to-end technical solutions and collaboration across teams.

Architect and lead enterprise data quality, observability, and validation frameworks for lead management systems. Own data integrity across ingestion, processing, and delivery pipelines; define data contracts, governance standards, SLAs, dashboards, and alerting. Diagnose systemic issues across distributed data flows, drive scalable architectural solutions, advise senior stakeholders, and mentor data engineers. Partner cross-functionally with Engineering, Product, and Data Science to improve reliability, customer fulfillment, and marketplace performance.

Supports client data and analytics engagements by designing validation approaches, building data integration and transformation solutions, analyzing data quality issues, testing pipelines with SQL, documenting findings, and recommending corrective actions. The role collaborates with clients, manages workstreams, mentors junior team members, and applies Agile methods while delivering risk and regulatory data solutions.

Lead product data engineering across architecture, data modeling, pipelines, monitoring, lineage, and data quality. Build reliable analytical datasets, support experimentation and machine learning use cases, and resolve business-critical pipeline issues. Partner with product and engineering stakeholders to translate business needs into automated data solutions. The role requires ownership of end-to-end data engineering projects, on-call participation, and development of AI-assisted monitoring and automation.

Owns PMO metrics, dashboards, and reporting infrastructure for aerospace programs. Develops Power BI dashboards, integrates data from multiple systems, standardizes KPIs, produces program reports, performs root-cause and trend analysis, and supports risk mitigation. Establishes data governance, tracks vendor performance, and serves as a liaison across engineering, manufacturing, quality, finance, and operations. Promotes self-service analytics and data-informed decision-making across the organization.

Lead product data engineering initiatives by designing data models, owning critical pipelines, building data quality and lineage monitoring, and supporting experimentation and ML-ready datasets. Translate business needs into automated data solutions, maintain pipeline SLAs through on-call support, and develop AI-assisted tools for issue detection and resolution. Collaborate with Product, Engineering, Data Science, Machine Learning, and Applied AI teams across Block’s products.

Own and build January’s foundational data systems, including end-to-end pipelines, data quality standards, legacy migrations, recovery processes, and documentation. Partner with engineers, analysts, operations, and product teams to establish trusted, scalable data infrastructure. Prioritize high-impact improvements, manage stakeholder needs, define ownership boundaries, and use AI to create increasingly self-healing systems.