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Build and maintain ETL/ELT pipelines, ensure data reliability, and create BI dashboards using Python, SQL, and tools like BigQuery and Airflow.
Builds and maintains scalable data pipelines, integrates diverse data sources, and ensures data quality and security for analytics and ML workflows using Python, SQL, Spark, and cloud tools.
Build and maintain Obat’s data pipelines and warehouse (BigQuery, Airflow, dbt) to power AI scoring and operational workflows for SaaS customers in the construction industry.
Build and maintain the data pipelines that power streaming-TV ad campaign reporting, ensuring accuracy and enabling new product features in a fast-growing AdTech startup.
Build and maintain the data pipelines that power Vibe.co’s streaming-TV ad reporting, ensuring accurate, real-time campaign metrics for advertisers.
Build and maintain robust data pipelines, ensuring quality and integrity, while collaborating with clients to optimize their data infrastructure using tools like Spark, Kafka, and cloud services.
Build and maintain the global data platform that powers Octopus Energy’s energy trading, forecasting, and risk operations using Python, SQL, Kubernetes, and AWS.
Build and maintain scalable cloud-based data pipelines using Modern Data Stack tools like BigQuery, DBT, and Airflow to enable AI-driven insights for enterprise clients.
Senior Data Engineer builds and maintains cloud-based data pipelines for enterprise clients, using Python, SQL, dbt, and Airflow to integrate, transform, and deliver reliable analytics-ready data.
Senior Data Engineer builds and maintains robust data pipelines, ensuring quality and integrity while collaborating with clients to optimize data infrastructure using tools like Spark, Kafka, and cloud services.
Build and deploy MLOps pipelines to collect robotics data, orchestrate model training, and automate deployment for AI-driven warehouse automation systems using Python, cloud infra, and Kubernetes.
Designs and builds scalable data pipelines in Python, SQL, dbt and Airflow, manages cloud data warehouses (BigQuery, Snowflake, Databricks), and explores generative AI to automate workflows for enterprise clients.
Senior Data Engineer builds and optimizes Snowflake-based data platforms on AWS, designing pipelines, transformations, and CI/CD workflows to industrialize modern data solutions.
Build and optimize large-scale data pipelines and distributed systems using Spark, Databricks, and AWS to power AI-driven B2B intelligence products.
Design and build scalable cloud data architectures (Snowflake, GCP/AWS/Azure) and robust ETL pipelines, then expose clean, governed data to analytics and AI teams using dbt and modern data-stack patterns.
Design and build modern data platforms, including pipelines, Lakehouse/Data Warehouse architectures, and cloud data solutions using Snowflake, Databricks, and Python/Spark.
Build and maintain modern Snowflake data platforms on AWS, including batch/real-time pipelines and dbt transformations, with Airflow orchestration and Terraform CI/CD.
Build and maintain robust data pipelines for a retail client, using Python, SQL, dbt, and GCP services like BigQuery and Airflow to ensure high-quality, production-ready data for BI and AI teams.
Build and maintain scalable data pipelines and models using Python, SQL, dbt, BigQuery, and Airflow to power analytics and reporting for a digital-offer platform.
Build and maintain scalable data pipelines and cloud infrastructure for a media company’s data platform using Python, Spark, SQL, GCP, Airflow, and Terraform.
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