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AWS Data Architect: Data Lake & Pipeline Champion
Designs and optimizes AWS-based data lakes and ingestion pipelines, modeling data in Redshift/RDS/DynamoDB while collaborating with analysts and solution architects.
GCP Data Architect & Engineer: Real-Time ELT Pipelines
Designs and operates scalable, secure GCP data pipelines using BigQuery and Dataflow to transform raw data into business insights.
GCP Data Architect & Engineer: Real-Time & Batch Pipelines
Designs and builds secure, scalable data pipelines on GCP to process real-time and batch data, turning raw data into actionable insights.
AWS Data Architect: Data Pipelines & Lakes on AWS
Designs and optimizes AWS-based data pipelines and lakes, collaborating with stakeholders to align data solutions with business outcomes while leveraging cloud-native tools and big data technologies.
Senior GCP Data Architect & Engineer - Real-Time ELT
Designs, builds, secures, and monitors real-time ELT systems on GCP to transform raw data into actionable business insights for decision-making.
AWS Data Architect - Lead Data Lakes & Pipelines
Designs and leads AWS-based data lake and pipeline architectures, collaborating with stakeholders to align technical solutions with business needs using cloud-native tools.
AWS Data Engineer — Cloud Data Platform & CI/CD Expert
Designs and builds AWS-based data pipelines, transforming and processing data for analytics and ML models while collaborating with stakeholders to define requirements and outcomes.
Senior Data Engineer — Build Scalable Pipelines for Impact
Designs and builds scalable data pipelines for fraud detection, cancer research, and national intelligence projects, collaborating with analysts and engineers to process diverse data sources.
Azure Data Engineer: Bridge Data Science & Engineering
Builds and maintains Azure-based data pipelines and lake loading for analytics and ML, collaborating with analysts and architects to deliver cloud-native solutions.
Azure Data Engineer: Bridge Data Science and Engineering
Designs and builds Azure-based data pipelines to ingest, clean, and load data for analytics and ML, collaborating with data scientists and architects.
Azure Data Engineer: Data Science Bridge & Big Data
The Azure Data Engineer will bridge data science and engineering by managing data acquisition, transformation, and loading into data lakes for analytics and machine learning. The role involves working in a cloud-native environment using Azure services, Spark, and Databricks.
Azure Data Engineer: Bridge Data Science & Big Data
Designs and builds Azure-based data pipelines and lake loading for analytics and ML, collaborating with analysts and architects in a cloud-native environment.
Azure Data Engineer: Bridge Data Science & Cloud Analytics
Designs cloud-native data pipelines and analytics solutions using Azure/Spark tools to bridge data science and engineering teams, translating business use cases into scalable data architectures.
GCP Data Architect & Engineer - Real-Time Data Pipelines
Designs and builds scalable, secure real-time data pipelines on GCP, transforming raw data into actionable insights using Java/Scala/Python and BigQuery.
Staff Data Engineer
Lead a small data engineering team to design, build, and scale WeRoad’s cloud-based data platform (BigQuery, dbt, Airflow) for travel experiences, focusing on real-time pipelines, self-service BI, and AI-driven insights across global markets.
GCP Data Engineer/Data Architect
The Data Architect designs and builds large-scale batch and real-time data pipelines on the Google Cloud Platform. The role involves managing data processing systems, ensuring security and scalability, and collaborating with business partners to drive data-driven insights.
Azure Data Engineer
Designs and implements cloud-native data pipelines, bridges data science and engineering, and optimizes data lakes for analytics/ML using Azure tools like Databricks and Synapse.
Data Engineer
Builds and maintains a Microsoft Fabric-based data layer that integrates multiple sources into versioned, auditable datasets for insurance risk models.