Remote Data Jobs · AWS

• Develop machine learning applications to support the new digital testing platform.
• Create insights from existing data and drive the collection of new data.
• Help the team break down the work into manageable tasks and support Agile maturity.

• Contributes to data analytics, data operations, and software product development.
• Supports existing data operations such as data refresh ETL and data structure development.
• Develops new products using data centric DevOps concepts to inform requirements and creation of APIs.

Coordinate and assist with deployment, support activities, database upgrades, and application of patches. Develop data migration plans and scripts, work with Oracle support on issues and bug fixes, manage tablespaces, account management, performance tuning, troubleshooting databases and debugging PLSQL. Plan and schedule maintenance including security patching and emergency responses for database management systems and platforms in the production environment.

Design, develop and optimize ETL pipelines using PySpark, Hive and Airflow for large-scale data processing. Build and maintain data lakes using Delta Lake, ensuring data reliability, quality, and integrity. Monitor, troubleshoot, and improve pipeline performance, scalability, and reliability.

• Develop and operate modern data architecture approaches to meet key business objectives.
• Develop intricate data processing pipelines, addressing clients' most challenging problems.
• Collaborate with data scientists to design scalable implementations of their models.

• Design, implement, and maintain AI systems.
• Develop AI evaluation modules, ensuring model observability, benchmarking, and performance monitoring.
• Build and optimize AI pipelines, data transformations, and metadata layers for clinical applications.

• Architect and build scalable infrastructure to transform large volumes of raw data into actionable insights.
• Design robust data pipelines, discovery systems, and lineage tracking platforms.
• Influence core data architecture and improve data accessibility and reliability.

Shape and evolve a modern, cloud-based data platform. Design and implement domain-oriented data products, optimize ETL/ELT pipelines. Build a robust data lake and support near real-time reporting and analytics.

Shape and evolve a modern, cloud-based data platform. Design and implement domain-oriented data products, optimize ETL/ELT pipelines. Build a robust data lake and support near real-time reporting and analytics.

Lead the assessment of new data sources, including coverage, quality, compliance, and commercial potential. Build and deploy statistical, predictive, and machine learning models to extract relevant insights from data. Lead client-facing meetings to present analytical findings, demonstrate product capabilities, and guide solution adoption.