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Senior Data Engineer builds and optimizes Google Cloud data pipelines for clients, using BigQuery, Dataflow, and Python to design scalable, reliable data architectures and datasets.
Builds and maintains data pipelines, Data Lake, and analytics infrastructure using Spark, Airflow, Delta Lake, and Parquet to support reporting and business decisions in an energy/utilities company.
Design and maintain data pipelines and models in Snowflake/DBT to feed analytics and AI initiatives for a global automotive manufacturer.
Build and maintain data pipelines and models for BI, ML, and AI systems at a fast-growing Italian telecom, using Python, SQL, and ETL tools.
Build and maintain data pipelines (ETL/ELT) using Python, Spark, and cloud services to feed analytics, AI, and ML initiatives for a leading Italian fintech company.
Designs, builds, and maintains scalable, high-performance data pipelines using Python, Spark, Hadoop, and Airflow for a product-focused team in Torino.
Design and maintain data pipelines in Snowflake and DBT to feed analytics and AI initiatives for Stellantis’ global supply chain and mobility operations.
Data Engineer builds and maintains ETL pipelines and data warehouses using Python, SQL, Spark, Databricks, and Airflow for clients in an IT consulting firm.
Build and optimize data pipelines, warehouses, and analytics platforms for an insurtech company using Python, Spark, Kafka, and AWS.
Build and maintain scalable data pipelines for a digital shopping marketplace using Spark, Kafka, and AWS to power real-time and batch analytics.
Designs, builds, and maintains scalable, high-performance data pipelines using Python, PySpark, and PostgreSQL for a product-focused team in Torino.
Build and maintain Java backend services with Spring Boot on AWS, integrating S3, SQS, and Aurora PostgreSQL while supporting DevOps workflows and cloud delivery.
Design and build scalable Snowflake and AWS-based data pipelines with Airflow orchestration to feed analytics and AI services for enterprise clients.
Builds and maintains Python-based ETL pipelines, cleans and transforms data using Oracle databases, and collaborates on system enhancements.
Lead the development of AI-powered data querying systems that let users ask business questions in natural language and return actionable insights, while building scalable data quality tools.
Build and maintain scalable ETL pipelines and data quality checks using Python, SQL, Apache Airflow, and dbt to support reliable data architecture.
Maintains and optimizes PostgreSQL databases, ensuring performance, security, and high availability for production systems.
Build and maintain scalable data pipelines and ETL processes using GCP tools like BigQuery and Dataflow, ensuring data quality and security.
Build and maintain data warehouses and pipelines to support analytics, using Python, SQL, dbt, Airflow, and GCP for a logistics platform.
Designs, builds, and maintains cloud-based data pipelines and warehouses to feed analytics and ML, using SQL, Python/Java/Scala, and tools like Airflow and Spark.
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