Top Data & Analytics Jobs

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.

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.

Supports reporting and optimization for Lowe’s Pro and Services business. The intern analyzes performance metrics, develops dashboards and reports, identifies process improvements, collaborates cross-functionally, and helps translate business insights into technical requirements and adopted solutions. The role provides experience in data visualization, analytics, sales enablement, operational excellence, and customer-focused decision-making.

Build and maintain Databricks data pipelines using SparkSQL and PySpark, integrating payer, provider, claims, platform, and API data. Develop transformations, models, file exchanges, dashboards, automated workflows, tests, and data-quality validations. Collaborate in design and code reviews, use AI coding tools responsibly, and protect PHI through governance, access controls, and audit logging.

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.

Design and maintain scalable data models, batch and streaming ETL pipelines, and end-to-end data workflows supporting business intelligence, machine learning, and operations. Ensure data quality, consistency, governance, traceability, and reliable delivery across distributed systems. Partner with business teams, platform engineers, and product managers to translate requirements into documented solutions and resolve data issues. The role is based in Seattle with three days per week in the office.