Top Data & Analytics Jobs

The Data Engineer will develop and integrate data pipelines, ensure data integrity, and support continuous automation in an Agile/Scrum environment.

The Global Senior Enterprise Architect aligns technology strategy with business goals, develops architectural standards, and communicates architecture solutions for manufacturing and quality processes in pharmaceuticals.

The role involves managing the lifecycle of data products and custom solutions, aligning with business needs, ensuring data governance, and engaging stakeholders.

The SAP Data Products Solution Owner develops strategies for SAP data assets, manages their lifecycle, ensures compliance with data governance, and aligns data products with business objectives.

The Senior Business Intelligence Analyst will develop reports and tools for analyzing sales and marketing performance and client service operations while collaborating with various leadership teams.

As a Solutions Analytics Data Scientist, you will analyze partner data, demonstrate product value, and provide actionable insights regarding fraud patterns and performance evaluations.

Develop sophisticated alpha-generating models, optimize portfolios, and enhance data analysis using quantitative techniques and advanced statistical methodologies.

The Credit Risk Manager will develop credit analytics frameworks, monitor portfolio health, drive product strategies, and automate risk processes, leveraging SQL, Python, and AI tools.

The Associate will build and support technology solutions for fund accounting, automate workflows, and ensure data quality in finance systems.

The Data Analysis Manager will lead analytics projects, mentor analysts, ensure data integrity, and deliver actionable insights to inform business decisions.

Lead and deliver finance solutions by collaborating with business, facilitating discussions, and overseeing SAP FICO processes and integrations. Responsible for project execution, risk management, and stakeholder engagement, ensuring alignment with strategic priorities and driving solution adoption across teams.

Lead design, build, and maintenance of scalable data pipelines and lakehouse infrastructure using PySpark, Databricks, and Airflow. Own data & ML platform (Terraform, Databricks), improve observability, data quality, and developer tooling, and partner closely with Data Science and engineering teams.