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Senior Data Engineer building and optimizing AWS and Databricks pipelines for JPMorgan Chase, focusing on scalable ETL, Spark/Databricks, and cloud cost governance.
Build and maintain business-focused data models and dashboards in Amazon QuickSight, mapping product data between systems and validating KPIs for decision-making.
Senior Data Engineer maintains and troubleshoots enterprise data pipelines on Azure, ensuring reliable data delivery for LATAM operations and analytics.
Senior Data Engineer builds and migrates data pipelines for a life-sciences CRM transition, using Databricks, AWS S3, dbt, and Airflow to move and transform Salesforce/Veeva data into a cloud data warehouse.
Build and optimize cloud-based data pipelines in Azure for healthcare analytics, using Azure Data Factory, SQL, and modern data architectures to support reporting and compliance.
Builds end-to-end data pipelines in Snowflake and AWS, transforming raw data into AI-ready features for an internal AI platform used across marketing and analytics workflows.
Lead the design and implementation of scalable Snowflake-based data ingestion and validation pipelines on AWS for an enterprise client, enforcing Medallion Architecture and data governance.
Senior Data Engineer builds and maintains scalable data pipelines in Snowflake and Python to process large datasets for analytics and reporting.
Senior Data Engineer maintains and troubleshoots enterprise data pipelines on Azure, ensuring reliable data delivery for LATAM reporting and analytics across business channels.
Build and maintain ETL pipelines in Microsoft Fabric to ingest mortgage data, enforce quality checks, and power analytics and compliance reporting.
Build and maintain scalable data pipelines and systems for a geolocation analytics platform, integrating diverse datasets and optimizing big-data infrastructure.
Build and optimize GCP-based data pipelines and vector databases to power AI models like LLMs and RAG systems for Doctolib’s AI Medical Companion, supporting healthcare professionals across Europe.
Build and maintain data pipelines, data marts in BigQuery with DBT, and dashboards in Tableau to power healthcare insights and AI strategy at a leading health-tech company.
Build and maintain data pipelines in Python (Dagster) and SQL/Jinja (DBT) to power analytics and AI at Doctolib, a healthcare platform.
Designs and builds secure data pipelines for large datasets, focusing on ETL, cloud data warehousing, and security-cleared environments.
Lead a backend and data engineering team to build a zero-hallucination AI platform using Python, Apache Beam, FastAPI, and Temporal on Google Cloud Spanner and graph databases.
Build and maintain Pennylane’s data analytics platform, designing scalable ETL pipelines and data models to power company-wide decision-making for 900k+ SMEs and accountants.
Build and optimize large-scale data pipelines and distributed systems using Spark, Databricks, and AWS to power AI-driven B2B intelligence products.
Build and scale AQEMIA’s data platform to power drug discovery, modeling chemical structures and experimental results with Python, SQL, Snowflake, and Airflow.
Build and maintain scalable data pipelines (ETL/ELT) using Python, SQL, Spark, and Airflow to feed BI, analytics, and data science teams.
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