Top Hybrid Data Engineer Jobs

Design, build, and support real-time event streaming platforms. Collaborate with teams to ensure scalable, reliable integration for data pipelines.

Lead a team to develop and maintain risk models, oversee model analytics, monitor performance, and collaborate with cross-functional teams. Utilize mathematical models and coding in R and Python for financial products.

The Senior Data Engineer will create scalable data pipelines and manage unstructured data for AI/ML workflows, ensuring data quality and supporting data solutions. Collaboration with cross-functional teams to meet business and security objectives is key.

Participate in a 10-12 week internship focusing on data engineering, including building data processing systems and learning Agile methodologies.

The Senior System Engineer will design financial data models and pipelines, support forecasting and reporting, and improve financial planning by integrating various enterprise applications and maintaining data quality.

As a Data Science Platform Engineer, you will build frameworks for predictive models, expand NLP analysis, and develop Java applications, while collaborating with the data science team.

The role involves designing risk controls, developing ML models, monitoring real-time risks, managing energy trading risk, and mentoring junior analysts.

The Python-ETL Data Developer will assist in onboarding client data into MySQL, support Snowflake offerings, and improve documentation. Key skills include Python and database experience.

The role involves leading ETL workflows and data integration for a pharmaceutical client, designing data solutions, optimizing performance on Snowflake, and collaborating with stakeholders to drive business value through data.

Lead the design and implementation of scalable data infrastructure and products. Collaborate with cross-functional teams to address complex data challenges and drive engineering best practices.