Top Data & Analytics Jobs

Designs, builds, and operates scalable batch, streaming, and real-time data platforms and pipelines. Responsibilities include data lake and warehouse development, cloud modernization, data quality, governance, security, observability, CI/CD, infrastructure automation, troubleshooting, architecture, and technical leadership. Partners with product, engineering, analytics, data science, and business teams to support reporting, marketing measurement, AI/ML, experimentation, and customer insights.

Builds and optimizes scalable data platforms, batch and streaming pipelines, data lakes, warehouses, models, and integration solutions. Leads technical designs, ensures security and governance compliance, owns end-to-end SDLC delivery, troubleshoots production issues, and mentors engineers. Collaborates with engineering, product, analytics, and business stakeholders to deliver reliable data products supporting analytics, machine learning, and business insights.

Leads the enterprise data architecture strategy, designing scalable platforms for secure data exchange, onboarding, discovery, and consumption. Establishes architecture standards, roadmaps, and engineering practices while adopting modern data and AI technologies. Partners with executives and global engineering teams, influences technical decisions, ensures governance and compliance, and mentors teams. The role requires deep expertise in large-scale data platforms, distributed systems, cloud and on-premises environments, and enterprise integration.

Lead the strategy, architecture, and evolution of enterprise data platforms supporting secure data exchange, discovery, governance, integration, and self-service consumption. Establish scalable patterns for data quality, lineage, observability, privacy, and security while reducing bespoke workflows through automation. Provide technical leadership across engineering organizations, influence architecture decisions, mentor technical teams, and translate complex business needs into reusable cloud and on-premises data solutions.

Designs and maintains scalable data pipelines, data quality frameworks, and cloud-native data solutions using Spark, Databricks, Hadoop, AWS, and advanced SQL. Implements validation, monitoring, observability, and automated remediation capabilities. Applies AI/ML, anomaly detection, and statistical modeling to improve data quality. Provides production support, resolves complex incidents, contributes to architecture and engineering standards, and collaborates with cross-functional data and engineering teams.

Leads the architecture, development, modernization, and operation of enterprise data platforms and pipelines supporting credit risk, analytics, regulatory reporting, and AI initiatives. Builds scalable cloud lakehouse solutions using Databricks, Spark, Delta Lake, Python, and SQL; establishes governance, quality, lineage, observability, and compliance controls; optimizes performance and costs; leads technical initiatives; influences architecture; mentors engineers; and partners with product, analytics, science, engineering, and business stakeholders.

Leads data analytics, engineering, reporting, visualization, and modeling initiatives across products, markets, and services. Builds dashboards, semantic models, performance metrics, and data quality controls using large-scale data technologies. Delivers actionable insights and executive-ready recommendations to cross-functional stakeholders, leads strategic analytical projects, and mentors or supervises junior analysts and data engineering talent.

Lead design and implementation of an Analytic Foundation and scalable big-data services delivered via APIs. Build data pipelines, analytics and data models, responsive UIs, and production ML/data-driven applications. Ensure high-quality, well-tested code, mentor junior engineers, drive process improvements, and collaborate with product and design teams to deliver customer-focused data solutions.