Top Hybrid Data & Analytics Jobs

Manage and scale paid media campaigns for gaming clients, optimize user acquisition strategies, and deliver insights to stakeholders.

Design, develop, configure, and support Customer MDM and Informatica Product 360 solutions, including data models, workflows, integrations, data quality, governance, and production support across enterprise systems. Collaborate with stakeholders throughout the SDLC to implement MDM/PIM processes, troubleshoot incidents, and maintain documentation and release activities.

Lead enterprise data management including governance, data quality, MDM, cataloging, and controlled distribution. Own policies, stewardship, MDM workflows (Reltio/SAP), vendor relationships, and metrics to improve master data trust, reduce duplicates, and enable faster onboarding. Coach stewards, partner with engineering/BI, and support audit, privacy, and compliance.

Build and scale Allocate's AWS-based data lakehouse and pipelines (batch and real-time). Model financial entities and integrate internal/third-party sources. Enable ML/AI workflows, vector and knowledge-graph integrations, CI/CD and containerized deployments, and collaborate with engineering to deliver reliable, production-grade data and AI infrastructure.

Lead enablement and coordination across domain teams to establish enterprise cloud data standards, platform onboarding, and data warehouse integration. Drive adoption of data engineering frameworks, reusable components, governance, data quality, stakeholder alignment, and continuous improvement to scale platform delivery across multiple teams.

Own and harden Plot's core data platform: stabilize high-throughput ingestion, design read-optimized schemas and partitioning, separate transactional vs analytical workloads, ensure performant data access for dashboards and AI agents, write RFCs, and raise reliability and observability across teams.

Maintain and evolve GMO's security master and portfolio data platforms (NeoXam DataHub, Aladdin, Eagle PACE). Analyze large datasets using Python, SQL, and Excel to identify data quality issues, define business requirements, support conversions/migrations, implement controls/automation, and collaborate with stakeholders to modernize data validation and onboarding processes.

The Data Entry Specialist will input and organize information about office buildings for landlords, ensuring data accuracy and optimizing property management efforts.

The Director of Data Science will lead credit risk modeling, oversee predictive modeling strategies, mentor data scientists, and ensure compliance with fair lending guidelines.

The Data Engineer will build and optimize data pipelines and infrastructure, ensuring data quality for analytics and machine learning initiatives while collaborating with teams to develop data solutions.