Remote Data Jobs · Python

• Lead the design and implementation of cloud-based data architectures.
• Work with cross-functional teams to develop scalable, secure, and efficient data solutions.
• Influence data strategy, mentor team members, and provide architectural guidance to stakeholders.

Lead technical strategy and enable enterprise clients to become more data-driven through advanced AI and ML solutions. Act as the main technical voice for key accounts, guiding organizations through transformational initiatives. Combine pre-sales expertise, technical leadership, and hands-on problem-solving to influence and deliver measurable business outcomes.

• 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.

Design, develop, and maintain Snowflake-based data pipelines and ELT workflows. Develop Snowflake objects, including tables, views, stored procedures, and UDFs. Monitor and optimize Snowflake performance using query profiling and workload management.

Transform complex data into strategic insights for financial institutions. Optimize marketing investments and enhance digital customer experiences. Deliver actionable insights to impact campaign performance and ROI optimization.

• 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.

Play a pivotal role in building foundational systems to manage data and AI assets. Design and implement scalable backend services, APIs, and data pipelines. Collaborate with engineers, product managers, and stakeholders to define requirements and deliver solutions.

• Design and implement large-scale data solutions for the mining industry.
• Build scalable data pipelines and analytics workflows using cloud platforms and AI/ML frameworks.
• Translate complex business requirements into robust technical solutions and mentor peers.

Maintain and optimize ELT pipelines to ensure reliable data flows. Develop and maintain scalable data models following best practices. Support data validation, testing, documentation, and governance across environments.

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.