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Own the lifecycle of a data-aware orchestration product, working with dbt, Airbyte, Snowflake, and Airflow to make pipelines easier to build, monitor, and scale for modern data teams.
Leads architecture and engineering of a healthcare-focused data platform, building scalable pipelines, warehouses, and AI-driven analytics to support clinical and business insights in a remote-first environment.
Builds and optimizes data pipelines for banks using Python, ETL tools (Informatica, Airflow, Spark), and databases (Oracle, ClickHouse) to support regulatory reporting and analytics.
Build and maintain scalable data pipelines and transformations using Python, SQL, dbt, and Snowflake to power BI, analytics, and AI initiatives in a modern DataOps environment.
Build and operate PayPay’s AWS-based data infrastructure using Terraform and Databricks, ensuring reliability, security, and smooth data workloads for the fintech platform.
Designs and maintains data pipelines in Snowflake and Databricks using Fivetran, dbt, and Sigma to deliver trusted insights and demo assets for a cloud analytics platform.
Lead the AI and data platform for a live-commerce marketplace, building pipelines, personalization, and automation systems that power buyer experiences, seller tools, and marketing campaigns using Python, ClickHouse, and LLMs.
Build and maintain the core platform that turns market data into features for AI-driven trading strategies, ensuring smooth research-to-production workflows and robust data pipelines.
Build and maintain the core platform that transforms market data into features for AI-driven trading strategies, ensuring reliable deployment and observability across research and production systems.
Build and maintain AI-powered search infrastructure for a learning platform, designing Elasticsearch pipelines, hybrid retrieval systems, and backend services to deliver low-latency, high-relevance results at scale.
Design and lead enterprise-scale data platforms (Lakehouse, Data Mesh) and ML pipelines using cloud tools (AWS/GCP/Azure), then mentor teams to deliver analytics and data products for ad-tech clients.
Build production-grade ML systems that detect retail crime patterns using computer vision, NLP, and graph analytics, deploying models on a cloud-native stack to power real-time alerts for global retailers.
Senior Data Scientist builds and optimizes scalable ETL pipelines with PySpark and Databricks, designs ML models for retail demand forecasting, and collaborates with stakeholders to deploy production-grade forecasting systems.
Build and maintain data pipelines with Estuary and dbt, write SQL and Python on Amazon Redshift to transform raw data into clean, tested datasets for analytics at Flutterwave.
Builds and maintains Figma’s data infrastructure, including Snowflake, ML Datalake, and streaming pipelines, to power analytics, AI/ML, and business intelligence across the company.
Senior Data Engineer builds and maintains automated data pipelines in Python, integrating with Snowflake and ServiceNow to ensure reliable data flow and system observability.
Build and own Hive’s cloud-native data and ML platforms handling billions of event-attendee interactions yearly, using Python, ClickHouse, Airflow, and LLM-powered pipelines to power real-time marketing automation for 1,500+ events.
Build and maintain scalable data pipelines and infrastructure to power analytics and insights for a fintech payments platform using Python, SQL, and cloud tools.
Build and own large-scale distributed data pipelines and storage systems using Airflow/Dagster, Spark, dbt, Kafka, and AWS to power global retail analytics.
Lead the design and scaling of distributed data pipelines and storage systems using Airflow/Dagster, Spark, dbt, Kafka, and AWS for a product-focused team.
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