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Lead a Data Engineering team at a global ad-tech DSP, building scalable pipelines, feature stores, and data-quality frameworks to power real-time bidding ML models in a high-growth mobile advertising platform.
Design and maintain a hybrid cloud data platform (AWS + GCP/BigQuery) for a European fintech, building data lakes, pipelines, IAM, and observability to power analytics and AI transformation.
Build and maintain secure, scalable cloud data platforms using Databricks, AWS services, and Terraform to enable governed data processing and analytics.
Build and maintain AWS data pipelines (Glue, Athena, Lambda) in Python, curate datasets for BI tools, and create dashboards using Power BI or Tableau.
Mid-level Data Engineer builds and maintains secure, scalable cloud data platforms using Databricks, AWS, and Terraform, focusing on governance, security, and efficient data processing.
Build and maintain ETL pipelines in Python to move and transform data, using SQL and AWS services like S3 and Athena.
Build and maintain the data platform that powers e-commerce insights: Snowflake, AWS lakehouse with Iceberg tables, Airflow pipelines, and Terraform IaC.
Build and optimize large-scale data pipelines using Scala/Spark and AWS to power analytics, ML, and reporting for a digital bank, ensuring reliable data flows for business decisions.
Build and maintain data pipelines on AWS using Spark, Python, and services like S3, EMR, and Glue to process batch and streaming data.
Design and build scalable data pipelines using Spark and cloud platforms to power analytics and ML for a leading digital bank.
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 scale cloud-based data pipelines and platforms using AWS, Python, PySpark, and Databricks to deliver reliable, high-performance data solutions for analytics and business needs.
Build and maintain cloud-based data platforms on AWS using PySpark, Python, and dbt to ingest, process, and orchestrate batch and streaming pipelines for clients.
Build and maintain large-scale data pipelines and cloud infrastructure using AWS, Spark/Scala, Python, and SQL to power analytics and ML workloads.
Lead the architecture of a cloud-based data platform on AWS, designing schemas and pipelines that power AI products and analytics using Terraform, dbt, and Iceberg.
Design and maintain scalable data pipelines and warehouses for a global ad-tech platform, ensuring real-time data availability and quality for analytics and decision-making.
Build and maintain data pipelines using Spark, PySpark, and AWS services to process batch and real-time data for clients.
Lead a data engineering team to build scalable analytics pipelines and models for a large European automotive marketplace, using Python, Spark, Airflow, and SQL.
Lead the architecture of a data platform on AWS, using Terraform and Apache Iceberg, to power AI products and analytics while mentoring a data engineering team.
Senior Data Engineer builds and scales reliable, high-quality data pipelines and governance at a global market-research analytics firm using Python, SQL, Airflow, Spark, and AWS.
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