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Build and automate ML pipelines on Databricks, ensuring data/model observability, SLA/SLO compliance, and CI/CD for scalable AI services in a product-focused team.
Build and own scalable data pipelines, cloud warehouse, and BI tooling using Python, SQL, dbt, Airflow, and Snowflake/BigQuery to turn product signals into business intelligence for a remote-first SaaS and AI company.
Build and deploy modern full-stack applications using React/Angular for SPAs and FastAPI/Flask/Node.js for backend services, with PostgreSQL databases.
Design and build scalable AWS-based data pipelines using Python, Spark, and cloud-native services to power analytics and reporting.
Build and optimize scalable data pipelines using Python, Spark, and AWS services like Glue, EMR, and S3 to power a modern data platform for financial indices.
Build and maintain scalable data pipelines and analytics platforms using Databricks, Spark, and cloud tools to power investment insights and reporting.
Build and optimize cloud-based data pipelines and analytics platforms using Databricks, PySpark, and Delta Lake to support real-time and batch processing for a fintech partner.
Build AI-powered document processing pipelines using OCR, VLMs, LLMs, and RAG to extract and index content from PDFs, images, and other files for enterprise AI assistants.
Designs and maintains scalable data pipelines using Azure Databricks and Azure Data Factory to ingest, transform, and optimize data for analytics and reporting, ensuring data quality, governance, and high performance.
Build and maintain data pipelines using PySpark, Python, and Azure Databricks; enforce governance in Unity Catalog and SQL Server; validate data quality and automate workflows.
Build and maintain data pipelines and applications using .NET (C#), Apache Spark, Databricks, and Delta Lake to process large-scale data efficiently.
Build and modernise cloud-native data platforms and pipelines for clients, using Python, SQL, and tools like Azure/AWS/GCP and Databricks.
Build and optimize cloud-native data platforms and pipelines for clients using Python, SQL, and tools like Azure Data Factory, Databricks, and Snowflake.
Senior Data Engineer responsible for conceptualizing data solutions, modernizing data environments, and building data pipelines using technologies like Microsoft Azure, Power BI, Python, and Fabric/Databricks. Works with clients and cross-functional teams to deliver actionable insights and optimize data infrastructure.
Design and govern enterprise AI architectures on Databricks, including MLOps pipelines, Unity Catalog governance, and generative AI use cases, while aligning with business objectives and compliance standards.
Principal Data Engineer – Databricks | Spark | Delta Lake | PySpark | Data Lakehouse | AWS/Azure Location: Toronto Work Model: Onsite (4 days/week) Key Requirements 12–18 years of overall Data Engineering experience.…
Build and maintain Azure-based data pipelines and analytics-ready datasets for Alberta’s environmental regulatory platform, using Databricks, Synapse, and Python to support compliance and decision-making.
Position: Data Engineer (AWS + Databricks) Location: Singapore Experience: 4 to 8 Years Key Skills Required Strong hands-on experience with Databricks Expertise in PySpark and Spark SQL Good experience with AWS Cloud…
Design and build scalable data pipelines using Spark, Flink, and Kafka to process real-time and batch datasets for B2B data products.
Senior Data Engineer at an Adtech company building and scaling a big data identity graph using Python, Spark, cloud platforms (AWS/GCP/Azure), and integrating AI/LLMs.
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