Top Data & Analytics Jobs

The Senior Data Analyst (Compliance) collaborates with business users to tailor solutions, creates reports and dashboards, conducts in-depth analyses, addresses data challenges, and champions data technologies to drive strategic decisions in financial compliance.

The Azure Data Engineer will provide technical expertise in developing and supporting data solutions, utilizing tools like Microsoft Fabric and Power BI. Responsibilities include ETL process development, operational data store design, implementing data improvement processes, supporting business intelligence solutions, and collaborating with stakeholders to meet data-related needs.

The Principal Scientist leads the Investigation & Remediation practice, building relationships with clients and overseeing project execution. Responsibilities include mentoring staff, preparing proposals, collaborating with project managers, and ensuring quality deliverables in environmental projects.

As a Senior Data Engineer, you will develop and maintain data pipelines using tools like Databricks and Airflow, write maintainable Python code, and design solutions with Kubernetes. You'll collaborate with Data Science teams to build scalable applications and manage data from diverse sources while ensuring effective communication across teams.

As a Senior Data Engineer (AI), you will design and maintain data pipelines, manage infrastructure, and integrate AI/ML applications. This role involves collaboration across teams to enhance data-driven decision-making and cybersecurity solutions.

As a FinTech Research Analyst, you will produce industry research reports, analyze market trends, manage proprietary databases, and assist in investment banking efforts while gaining exposure to senior professionals in a boutique investment bank setting.

As a Staff Analytics Engineer at Amplify, you will work within data analytics teams to create data models and metrics, enhance processes, and provide insights for educators. Your responsibilities include building analytical models, ensuring data privacy while analyzing performance, and collaborating with data specialists to enhance data practices.