Top Data & Analytics Jobs

The Business Analyst will elicit and document requirements, create user stories, and perform functional testing in an agile environment. Responsibilities include managing sprints, conducting user acceptance testing (UAT), and coordinating with business users and development teams.

The Senior Data Analyst will define data sources for insights, determine data mappings across multiple sources, highlight data inconsistencies, assist with data migration, and manage stakeholder expectations. A strong analytical background and experience in financial services, particularly with data models and risk analysis, is essential.

The Sr. Data Engineer will work on financial services projects using PySpark and Scala with a focus on debugging and data analysis. The role requires understanding of SDLC, experience with Big Data application life cycles, and proficiency in GIT, with bonus skills in CICD tools like Jenkins and Ansible.

As a Senior Data Engineer at Capco, you will design and optimize data pipelines, manage data analytic solutions, ensure data quality, and innovate with emerging technologies. Your role will involve leveraging big data technologies, creating ETL workflows, and maintaining security and compliance standards.

The role requires a strong Business Analyst with experience in Regulatory and Data Privacy projects. Responsibilities include detailed requirement gathering, stakeholder management, and familiarity with legal/compliance text. Experience with Agile tools like Jira and Confluence is necessary, along with preferred experience in Banking, Financial Services, and Insurance.

The Credit Risk Analyst will conduct credit risk assessments for corporate clients, analyze financial statements, monitor compliance with credit policies, collaborate with teams to optimize credit risk models, and communicate findings in either German or French. The role demands 2-3 years of credit risk analysis experience and fluency in one of the specified languages.

The Mid Big Data Engineer will design, implement, and maintain scalable data pipelines using Scala, Spark, and Hadoop for large-scale data processing and analytics. Responsibilities include optimizing data workflows, ensuring data quality, and providing mentorship to team members.