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Build and maintain scalable data pipelines and warehouse models that power AI-driven matching and recommendation systems for a climate-focused upskilling platform.
Build and maintain scalable data pipelines and infrastructure to support analytics, reporting, and AI initiatives for Teladoc Health Canada’s virtual care platform.
Senior Data Engineer at Springfinancial designs and maintains scalable data pipelines for financial products, ensuring reliable data access and collaborating with data scientists and engineers.
Build data pipelines and a knowledge graph to unify messy engineering data (BIM, PDFs, spreadsheets) into a queryable system for AEC firms.
Build and optimize scalable data pipelines, ML workflows, and AI systems on Databricks using Spark, Delta Lake, MLflow, and Mosaic AI.
Design and run rigorous tests for Veeva’s AI agents, curating adversarial prompts and automating evaluation pipelines to catch hallucinations, biases, and edge cases in LLM outputs.
Lead a team of data engineers to build and maintain scalable data pipelines and warehouses using SQL, Python, Snowflake, and DBT for a fast-growing Canadian dental healthcare network.
Lead and build cloud data pipelines using Python, PySpark, SQL, and Databricks for enterprise banking systems, ensuring efficient ingestion, transformation, and analytics at scale.
Designs and maintains scalable data pipelines and ETL processes using SQL, Python, and Google BigQuery to support retail and e-commerce analytics in GCP.
Build and maintain ETL pipelines in Databricks for a Capital Markets data hub, setting standards and enabling clean data flows across teams.
Designs and maintains data pipelines, optimizes SQL schemas, and ensures reliable ETL processes for analytics and reporting.
Build and optimize data pipelines and lakes for AI systems, focusing on RAG architectures and data quality to support machine learning research and analytics.
Designs and maintains data infrastructure, ETL pipelines, and cloud-based warehouses to support analytics and reporting for a construction/infrastructure-focused company.
Build and own the real-time data pipelines and infrastructure that feed AI models for a biotech platform, integrating customer systems and ensuring clean, reliable data at scale.
Build and secure Snowflake and AWS data infrastructure, automate provisioning with Terraform, and implement RBAC and governance for regulated financial analytics.
Leads a team building scalable data platforms on Azure/AWS, using Spark, Hadoop, and Airflow to power enterprise analytics and AI solutions.
Lead a team to design and build data pipelines and warehouses for enterprise clients, using Python/Java/Scala, cloud platforms, and ETL tools.
Design and build end-to-end data pipelines and models for risk analytics at a major Canadian bank, using Python, SQL, and modern data tools.
Build and optimize scalable data pipelines and lakehouse solutions using Databricks, Apache Spark, and Delta Lake, integrating with downstream systems for real-time and batch data consumption.
Build and own Jane’s customer data infrastructure from the ground up: event pipelines, CDP tooling, identity resolution, and attribution systems that power marketing and product decisions across thousands of clinics.
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