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Analyzes B2C marketing data to track performance, identify growth opportunities, and drive data-driven decisions for a digital media company. Focuses on attribution, tracking, and building AI-powered tools for marketing teams.
The Data Engineer will design, build, and maintain custom data pipelines and infrastructure to support reporting, operations, and AI initiatives. The role involves working with Python, SQL, Airflow, and dbt to ensure data quality and reliability in a remote-first environment.
The Senior Data Engineer will design, build, and maintain scalable ETL/ELT pipelines within GCP environments. The role involves implementing data transformation logic, ensuring data quality, and collaborating with cross-functional teams to deliver scalable data solutions.
Design and maintain enterprise-scale data pipelines in Snowflake using Airflow for orchestration and dbt for transformation.
Designs, develops, and optimizes cloud-based data platforms using Snowflake, SQL, and tools like Apache Airflow and dbt to build scalable ELT pipelines and support enterprise analytics.
Designs and optimizes cloud-based data platforms using Snowflake, Airflow, and dbt to build scalable ELT pipelines and data models for enterprise analytics.
Build and maintain Snowflake-based data pipelines using Apache Airflow and dbt, optimizing SQL queries and modeling data for analytics.
Designs and maintains batch/streaming data pipelines for AI/ML products, fraud detection, and personalization, collaborating with data scientists and backend engineers using PySpark, Kafka, Databricks, and Airflow.
Lead the technical direction of analytics engineering for Vinted’s revenue, purchase, and orders domains, building scalable, maintainable data models and pipelines using SQL, dbt, and cloud platforms like BigQuery.
Build and maintain Databricks data pipelines (PySpark, SQL) that feed analytics products for LATAM supply-chain teams, using medallion architecture and AI-assisted tools.
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Build and maintain scalable data pipelines and warehouses for a fast-growing mobility app, using Python, Spark, Kafka, and cloud data warehouses like Snowflake.
Designs and maintains scalable data pipelines and warehouses for mobility services, collaborating with analysts to ensure reliable data delivery and support data-driven decisions.
Builds and owns full-stack features across a layered platform, including React frontends, GraphQL APIs, AI-driven intelligence, and data services, with end-to-end ownership from concept to production.
Build and maintain scalable GCP data pipelines using BigQuery and Airflow, ensuring performance and reliability while collaborating with analytics and product teams.
Build, automate, and secure a GCP-centric cloud platform using GKE, Airflow, Terraform, and CI/CD pipelines in a fast-paced startup environment.
Senior data engineer builds and maintains a data platform for a Brazilian education company, using distributed processing, cloud infrastructure, and modern data stack tools.
Build and maintain AI-driven data products like agents, chatbots, and automated query systems for an edtech company, using Python, SQL, and cloud tools.
Machine Learning Engineer (hybrid, Warsaw) building production-grade Python ML applications, MLOps pipelines on GCP/Azure, model-serving systems, and GenAI/LLM deployments for Harvey Nash Technology's clients.
Design, build, and maintain scalable ETL/ELT data pipelines to transform raw data into insights for analytics/business teams, using Python, SQL, and tools like Airflow/Prefect/Dagster in a cloud data stack (Snowflake/BigQuery/AWS Redshift/Databricks).
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