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Build and maintain a modern data platform in AWS/Snowflake using Python, SQL, Airflow/dbt, and Terraform to power analytics and reporting for a crypto/fintech platform.
Build and maintain scalable, reliable data infrastructure and AI pipelines using Terraform, Python, and streaming tech to power Flywire’s global payments and AI strategy.
Lead a data engineering team to build and optimize scalable pipelines in BigQuery using dbt and Airflow, supporting AI-driven analytics for millions of events.
Design and build scalable data pipelines using Spark and cloud platforms to power analytics and ML for a leading digital bank.
Build and maintain data pipelines on GCP, using BigQuery, Python, dbt, and Prefect to ingest, transform, and activate data from CRM, ecommerce, and digital campaigns.
Build and optimize large-scale data pipelines using PySpark/Scala and AWS services to power analytics, ML, and reporting for a leading digital bank.
Build and maintain scalable data pipelines and ETL workflows using Python, Airflow, and SQL, ensuring robust data ingestion and validation for downstream systems.
Builds and maintains a distributed data pipeline that cleans, transforms, and serves vulnerability and exposure data in near real time using PySpark, Airflow, dbt, and AWS.
Builds and maintains scalable data pipelines and lakehouse architectures to feed BI, analytics, and AI workloads using SQL, Python, and cloud platforms.
Lead the design and optimization of iRESTORE’s BI stack, including BigQuery, Looker Studio, and dbt pipelines, to enable data-driven decisions across marketing, operations, and logistics.
Build and maintain data pipelines, clean and transform datasets, and integrate data flows into backend services and dashboards using Python, SQL, and orchestration tools.
Lead the architecture and delivery of large-scale healthcare data pipelines and platforms for Roche’s digital cervical screening solution, using Python, SQL, Spark, and cloud data tools.
Build and optimize data pipelines for an AI-driven orthodontic clinic network, transforming raw data into insights with dbt, SQL, and Python while collaborating with product and ML teams.
Build and maintain cloud-based data pipelines using ETL/ELT, SQL, Python, dbt, Airflow, and Spark in a product-focused team.
Build and maintain scalable data pipelines in Google Cloud using Airflow, dbt, BigQuery, Pub/Sub, and Snowflake to enable reliable data ingestion, transformation, and analytics.
Build and maintain AI-driven data pipelines for financial crime detection at a fintech company using Spark, Python, and big-data tools.
Build and maintain ETL pipelines in Python and Airflow to ensure clean, traceable data flows for analytics and decision-making.
Build and maintain data pipelines in Python and Airflow to ensure BigQuery data remains accurate and traceable for a European scale-up.
Build and optimize Snowflake data pipelines and dbt models for analytics, applying ELT, Kimball modeling, and CI/CD practices in a cloud environment.
Build and maintain cloud-based data pipelines and analytics platforms using Python, SQL, Spark, and BigData tools to deliver business insights.
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