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Senior Data Engineer builds and scales a modern data platform using Python, Snowflake, Airflow/Prefer/Dagster, and CI/CD for reliable ETL/ELT pipelines and DataOps.
Senior Data Engineer builds and scales modern data pipelines, optimizes Snowflake warehouses, and implements DataOps practices using Python, Airflow/Prefect/Dagster, and CI/CD.
Lead a team to design and maintain large-scale ETL pipelines and OLAP data architecture on AWS, using S3 data lakes, Athena, Airflow, and Python, while enforcing code quality and guiding senior developers.
Build and deploy scalable data pipelines, cloud infrastructure, and full-stack apps that expose AI models and processed data for enterprise clients.
Build and maintain Nutripure’s data platform on GCP, ensuring reliable, fresh data pipelines and enabling analysts with clean models and observability.
Builds and maintains scalable data pipelines and workflows in GCP for defense AI systems using Python, SQL, and Prefect.
Senior Data Engineer builds and governs robust data pipelines and architectures for AI agents in finance, public sector, luxury, and healthcare, ensuring reliability and scalability for production use.
Designs and scales data infrastructure (lakes, warehouses, pipelines) using Spark, Kafka, ClickHouse, and PostgreSQL, while leading a team of data engineers and collaborating with data scientists and DevOps.
Build and maintain cloud-based data pipelines in Python and SQL, design modern data platforms (Data Lake, Warehouse), and ensure data quality and observability for analytics and AI projects.
Designs and builds scalable data pipelines, cloud data architectures, and ETL/ELT processes for AI and ML projects at major enterprise clients.
Build and deploy scalable data pipelines, cloud infrastructure, and full-stack apps that expose AI models and datasets for analysts and scientists.
Build and scale Vibe’s petabyte-scale data backbone, owning storage, batch/stream compute, and real-time OLAP reporting to power streaming-TV ad campaigns.
Build and maintain Chance’s data stack: migrate PostgreSQL to ClickHouse, set up pipelines with DBT/Airbyte/Prefect, and ensure reliable analytics for a dating platform.
Build and maintain scalable data pipelines using Python, SQL, Spark, and cloud services (Azure/AWS/GCP) to deliver clean, reliable datasets for analytics and AI teams.
Build and scale Vibe’s petabyte-scale data backbone, owning storage, batch/stream compute, and real-time OLAP reporting to power streaming TV ad campaigns.
Build and maintain petabyte-scale data infrastructure using Spark, ClickHouse, and lakehouse tools, and own incident response and cost optimization for real-time reporting.
Build and maintain scalable data pipelines and warehouses for analytics, using cloud tools like AWS and Snowflake, orchestration platforms such as Airflow, and data modeling best practices.
Design and scale backend services, APIs, and data pipelines for AI-powered media workflows, integrating generative models and optimizing performance.
Build and scale ML infrastructure for a quantitative trading firm, designing feature stores, MLOps pipelines, and data lakes to support petabyte-scale time-series models in low-latency environments.
Build and maintain scalable Python-based backend services, ETL pipelines, and scrapers using Django/FastAPI, PostgreSQL, AWS, and Redis to power data-driven business decisioning solutions.
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