Top Senior Data & Analytics Jobs

Lead analytics efforts by building data solutions, developing dashboards, performing analysis for business insights, and ensuring data quality, governance, lineage, and secure access. Use scripting, Snowflake, and BI tools to enable self-service and support cross-functional stakeholders.

The Senior Manager leads card data management, ensuring data quality, compliance with policies, and driving automation and risk oversight through team collaboration and innovation.

Lead validation of enterprise-wide analytical tools for risk management: plan and execute validation projects, assess methodology quality and tool risk, prototype best practices, communicate findings, and coach junior staff.

Lead enterprise data modeling and architecture for the firm's lakehouse and Fabric platform. Define canonical data models, produce ERDs and dimensional schemas, govern Silver/Gold layers, run design reviews, document ADRs, and align data governance, lineage, security, and data contracts to ensure trusted analytics and self-service consumption.

Support Business Banking with analytics, reporting, dashboards, and automation to drive deposit acquisition, onboarding, funded balance growth, and retention. Produce forecasting and pipeline reporting, provide deposit strategy and profitability insights, enable go-to-market and campaign analysis, and standardize onboarding and data processes to improve efficiency and data quality.

Design, build, and maintain scalable Spark/SQL data pipelines and ETL/ELT frameworks for batch and real-time processing. Deploy and manage containerized data workloads on Docker/Kubernetes/OpenShift, manage data lakes on object storage (S3/ADLS) using formats like Apache Iceberg, implement CI/CD for data workflows, optimize Spark performance, drive architecture and modernization, ensure governance/compliance, and provide technical leadership and mentorship.

The Data Architect Sr designs and optimizes data warehouses, analyzes BI data, develops architecture requirements, and ensures data quality and integrity in support of business processes.

Lead design, build, and operation of scalable, secure GCP data platforms and reusable frameworks (ingestion, transformation, orchestration). Enable self-service analytics, enforce governance, data quality, observability, and security controls. Partner with domain teams, document patterns, and contribute to roadmap and tool selection.

Lead design and implementation of enterprise internal employee fraud detection rules and proactive monitoring. Use advanced analytics (SAS, SQL) to identify emerging threats, recommend rule enhancements, and partner with senior leaders, Risk, Compliance, and Technology to ensure effective, auditable controls and scalable detection solutions.

Lead design, build, and operate scalable, secure GCP data platforms and reusable data frameworks (ingestion, transformation, orchestration). Enable self-service, governance, data quality, observability, and cost/performance optimization. Partner with domain teams, document runbooks, and contribute to platform roadmap and CI/CD integration.

Manage production operations for the Enterprise Decision Engine: monitor alerts and performance, troubleshoot incidents, perform impact/root-cause analysis, coordinate cross-functional responses, document processes, and advise on decisioning tactics, business rules, and optimizations to improve personalization and omni-channel campaigns.

Lead measurement and analytics for video advertising: design and run incrementality and quasi-experimental studies, pilot first-party measurement, conduct deep campaign analyses, partner with product/engineering and sales, and translate findings into actionable recommendations for clients and internal stakeholders.

Build and maintain dashboards and ETL pipelines to standardize logistics and packaging data, perform exploratory analysis and root-cause investigations, identify cost and efficiency opportunities, and deliver actionable insights to cross-functional stakeholders to improve inbound execution, pack density, and cost visibility.

Design, build, and deploy Python data pipelines and CI/CD workflows to produce business data objects. Implement source-to-target mappings, perform unit and integration testing, troubleshoot complex application issues, and promote software quality and team improvements.

As a Senior Data Engineer, you will implement data ingestion patterns, build pipelines in Azure, and enhance development with AI tools, aiding the migration to a cloud-based architecture.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.