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Build and deploy scalable data pipelines and MLOps workflows to integrate structured, semi-structured, and unstructured data for GenAI and LLM solutions in the insurance sector.
Build and maintain data pipelines and infrastructure for AI solutions, working with Spark, Python, and LLMs to support machine learning models and predictive analytics.
Builds scalable ELT pipelines in BigQuery and dbt for public transit data, integrates real-time GTFS feeds, and delivers QlikSense dashboards for agencies and stakeholders.
Designs and builds cloud-based ETL pipelines and data infrastructure on Azure/GCP, working on migrations and modernizations for global clients.
Build and curate insurance data assets, integrate GenAI for data quality, and deliver Power BI dashboards to support underwriting and claims decisions.
Design and optimize scalable data pipelines using Databricks, Apache Airflow, and Spark to process streaming and batch data for enterprise clients across industries like aerospace, energy, and automotive.
Design and build ETL/ELT pipelines using Informatica and Microsoft Azure tools, migrating enterprise data to cloud-based Microsoft Fabric and integrating AI services like Azure OpenAI.
Senior Data Engineer/ML Engineer builds and deploys ML models and pipelines in a banking context using Python, Spark, and AWS services like SageMaker and Glue.
Build and optimize scalable data pipelines using Databricks, Spark, and Azure to power AI/ML solutions for global enterprises across aerospace, energy, and automotive sectors.
Design and implement Microsoft Fabric and Azure-based data pipelines, ETL/ELT processes, and AI-driven analytics solutions for enterprise clients.
Senior Data Engineer designs and builds scalable data pipelines and warehouses, mentors junior engineers, and ensures reliable data delivery for analytics and business insights.
Senior Data Engineer builds and transforms financial data pipelines for credit compliance systems, migrating legacy warehouses to Databricks and enabling analytics dashboards.
Build and maintain scalable ETL pipelines and data models using Spark, Scala, and cloud storage, then deliver clean data to analytics teams via BI tools like Databricks and Power BI.
Senior Data Engineer builds and maintains data pipelines and models for a fintech platform, migrating legacy systems to Databricks and PySpark while ensuring regulatory compliance and delivering analytics dashboards.
Design and build scalable ETL pipelines and data models using Spark, Scala, and cloud storage (AWS S3, Hive) to support analytics and BI tools like Databricks and Power BI.
Designs and builds cloud-based data pipelines and ETL workflows on Azure or GCP, using Python/Java/Scala, Spark, Kafka, and Airflow to modernize and migrate enterprise data systems.
Design and build scalable ETL pipelines and data models using Spark, Scala, and cloud storage (AWS S3, Hive) to power analytics and BI tools like Databricks and Power BI.
Build and optimize Apache Spark data pipelines and SQL queries for financial and logistics clients in a hybrid Warsaw role.
Build and optimize GCP-based data pipelines and ML models, then visualize insights in Looker Studio to drive TELUS’s operational and customer-experience improvements.
Design and maintain a cloud-based lakehouse on AWS, building real-time ingestion pipelines with Kafka/Debezium and PySpark, and curating trusted analytics layers for fintech decision-making.
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